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Steven Katz MSIV

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PART 1: BIOSTATISTICS

Terms:

Independent variable: values that are controlled orselected by the person experimenting to determineits relationship to an observed phenomenon (thedependent variable).

Dependant variable: the observed phenomenon,usually cannot be changed.

In summary:

Independent variables answer the question "What doI change?"

Dependent variables answer the question "What do Iobserve?"

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Types of Studies (p.60)

Case Control: Compares a group of people with

a disease to a group without.Asks what happened?

Two types:

Observational and Retrospective

Famous example is lung cancer link to smoking

Issues: Confounding: a variable that correlates to both

dependant and independent variables. Cannot prove cause and effect of risk factor to

variable

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Types of Studies (p.60)

Cohort: Compares a group with a given riskfactor to a group without

Assesses whether the risk factor increases the

likelihood of disease

Asks what will happen

Two types:

Observational and Prospective

Used to prove cause and effect of smoking to

lung cancer.

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Types of Studies (p.60)

Cross-Sectional: Collects data from a

group of people to assess FREQUENCY

of disease (and related risk factors) at a

particular point in time.Asks what is happening?

Example: political polls

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Types of Studies (p.60)

Twin Concordance: Compares the

frequency with which both monozygotic

twins or both dizygotic twins develop a

disease Measures heritability

Example: look at incidence of diabetesin twins

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Types of Studies (p.60)

Adoption: Compares siblings raised by

biologic v. adoptive parents

Measures heritability and influence of

environmental factors

Famous examples are Swedish

adoption studies

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Clinical trials (p.60)

Experimental study involving humans.

Compares therapeutic benefits of 2 or

more treatments, or of treatment and

placebo. Highest quality study is double-blind

randomized control trial.

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Clinical trials (p.60)

Study Sample Purpose

Phase I Small number of pts,usually healthy volunteers

Assess safety, toxicity,

and pharmacokinetics

Phase II Small number of pts withdisease of interest

Assesses treatmentefficacy, optimal dosing,

and adverse effects

Phase IIILarge number of pts

randomly assigned to eitherthe treatment under

investigation or to the best

available treatment (or

placebo)

Compares the new

treatment to the currentstandard of care.

Is more convincing if

double-blind

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Meta-analysis (p.60)

Pools data from several studies to come

to an overall conclusion.

Achieves greater statistical power and

integrates results of similar studies

Highest echelon of clinical evidence

May be limited by quality of individual

studies or bias in study selection

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Evaluation of diagnostic tests (p.61)

2 x 2 table (TN = True neg, TP = True pos, FP

= false pos, FN = false neg)

DISEASE

TEST

+ -

+ TP FP

- FN TN

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Evaluation of diagnostic tests (p.61)

Sensitivity = TP/(TP+FN) = 1-FN rate Proportion of all people with disease who test

positive

Value approaching 1 is desirable for RULINGOUT disease and indicates low false negativerate.

Used for SCREENING in diseases with lowprevalence

SNOUT = SeNsitivity rules OUT If sensitivity = 100% then all negative tests

are TN (TP/(TP+FN) = 1) because FN = 0

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Evaluation of diagnostic tests

(p.61)

Specificity = TN/(TN+FP) = 1-FP rate

Proportion of all people without disease who test

negative

Value approaching 1 is desirable forRULINGINdisease and indicates a low FP rate

Used as a CONFIRMATORY test after a positive

screening test

SPIN = SPecificity rules IN If specificity = 100% then all positive tests

are TP (TN/(TN+FP) = 1) because FP = 0

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Evaluation of diagnostic tests

(p.61)

Positive Predictive Value (PPV) =

TP/(TP+FP)

Proportion of positive tests that are true

positives Probability that a person actually has the

disease given a positive test result

Note: If the prevalence of a disease islow then even tests with high specificity

or sensitivity will have LOW PPV

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Evaluation of diagnostic tests (p.61)

Negative Predictive Value (NPV) = TN

/(TN+FN)

Proportion of negative tests that are true

negatives Probability that a person actually is disease

free given a negative test result

http://gim.unmc.edu/dxtests/bayes.htm

http://gim.unmc.edu/dxtests/bayes.htmhttp://gim.unmc.edu/dxtests/bayes.htm

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Evaluation of diagnostic tests (p.61)

A = 100%

sensitivity

B= most

accurate

C = 100%

specificity

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Prevalence v. Incidence (p.62)

Prevalence = TOTAL cases in a population at a given timetotal population at risk at a given time

Incidence = NEW cases in a population over a time periodtotal population at risk during that time

Prevalence = incidence X disease duration

Prevalence > Incidence for chronic dzs

Prevalence = incidence for acute dzs

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Odds ratio (p.62)

For case control studies

(a/b)/(c/d) = ad/bc

Odds of having disease in exposed group

divided by odds of having disease inunexposed group

Approximates the relative risk if prevalence

of disease is not too high

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Relative risk (p.62)

For cohort studies

Relative probability of getting a disease

in the exposed group compared to the

unexposed group [a/(a+b)]/[c(c+d)]

Calculated as a percent of exposed pts with

dz to unexposed pts with dz

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Attributable risk (p.62)

The difference in risk between exposedand unexposed groups

OR

The proportion of disease occurrencesthat are attributable to the to theexposure

(e.g. smoking causes 1/3 of cases ofpna)

[a/(a+b)] [c/(c+d)]

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Odds ratio, relative risk, attributable risk

(p.62)

Disease

RiskFactor

+ -

+ a b

- c d

Attributable risk = [a/(a+b)] [c/(c+d)]

Odds ratio: (a/b)/(c/d) = ad/bc

Relative Risk: [a/(a+b)]/[c(c+d)]

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Precision v. accuracy (p.62)

Precision:

The consistency and reproducibility of a test

RELIABILITY

The absence of random variation in a test Random Error: reduced precision in a test

Accuracy: The trueness of test measures

VALIDITY

Systematic error: reduced accuracy in a test

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Precision v. accuracy (p.62)

Neither Precise Nor Accurate

This is a randomlike

pattern, neither

precise nor accurate.

The darts are not

clustered together and

are not near the bull's

eye.

Precise, Not Accurate

This is a precise

pattern, but not

accurate. The darts

are clustered

together but did not

hit the intended

mark.

Accurate, Not Precise

This is an accurate

pattern, but not

precise. The darts

are not clustered,

but their 'average'

position is the

center of the bull's

eye.

Precise and Accurate

This pattern isboth precise and

accurate. The

darts are tightly

clustered and their

average position is

the center of the

bull's eye.

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Bias (p.63)

Occurs when 1 outcome is systematically favoredover another

Systematic errors: Selection bias: nonrandom assignment to study group

Recall bias: knowledge of presence of disorder alters

recall by subjects Sampling bias: subjects are not representative relative to

general pop; therefore, results are not generalizable

Late-look bias: information gathered at an inappropriatetime

Procedure bias: subjects in different groups are nottreated the same E.g. more attention is paid to treatment group, stimulating greater

compliance

Lead time bias: early detection confused with increased

survival

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Bias (p.63)

Confounding bias: occurs with 2 closely associatedfactors The effect of the 1 factor distorts or confuses the effect of the other

Pygmalion effect: occurs when a researchers belief inthe efficacy of the treatment changes the outcome of thattreatment

Hawthorne effect: occurs when the group being studiedchanges its behavior to meet the expectations of theresearcher

Ways to reduce bias:

Blind studies Placebo responses

Crossover studies (each subject is its own control)

Randomization

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Statistical distribution (p.63)

Normal, Gaussian, bell-

shaped curved

Mean = mode = median

Bimodal = 2 humps

Positive skewmean

>median>mode

Asymmetry with tail on right

Negative skew

mean

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Statistical hypotheses (p.63)

Null (H0): Hypothesisof NO DIFFERENCE e.g. there is no

difference between the

dz and the risk factor inthe population

Alternative (H1):Hypothesis that the is

some difference e.g. there is some

association between thedz and the risk factor inthe population

Reality

Study

Results

H1 H0

H1Power

(1-b) a

H0 b

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Error types (p.64)

Type I error (a): Stating that there IS an

effect or difference when none exists (to

mistakenly accept the experimental

hypothesis and reject the nullhypothesis)

p = probability of making a type I error

p is judged against a, a preset level ofsignificance (usually

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Error types (p.64)

Type II error (b): Stating that there is

NOT an effect or difference when one

exists (to fail to reject the null hypothesis

when in fact H0 is false) b is the probability of making a type II error

False negative error

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Error types (p.64)

Ifp < 0.05 then there is a less than 5%

chance that the data will show

something that is really not there.

a= you saw a difference that did notexist

b= you did NOT see a difference that

does exist

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Power (1-b) (p.64)

Definition:1. Probability of rejecting a null hypothesis when it is in

fact false

2. The likelihood of finding a difference if one in factexists

Depends on:1. Total number of endpoints experienced by the

population

2. Difference in compliance between treatment groups

(diff in the mean values of the groups)3. Size of expected effect

If you increase sample size you increase power

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Standard deviation v. standard error

(p.64)

n = sample size

s = standard deviation

SEM = standard error

of the mean

SEM = s/square root

(n)

Therefore, SEM < sandSEM decreases as n

increases

http://en.wikipedia.org/wiki/File:Standard_deviation_diagram.svghttp://en.wikipedia.org/wiki/File:Standard_deviation_diagram.svg

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t-test v. ANOVA v. c2 (p.65)

t-test checks difference between the MEANS of

2 groups

Mr. T is MEAN

ANOVA checks difference between the means

of 3 or more groupsANOVA =ANalysis OfVAriance of 3 or more

variables

c2

checks difference between 2 or morepercentages or proportions of categorical

outcomes (NOT mean values)

c2 = compare percentages or proportions

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Correlation coefficient (r) (p.65)

r is always between -1 and +1.

The closer the absolute value of r is to 1,

the stronger the correlation between the

2 variables

Coefficient of determination = r2 (value

that is usually reported)]

Provides a measure of how well futureoutcomes are likely to be predicted by the

model.

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Disease prevention (p.65)

1o prevent disease occurrence (e.g.

vaccination)

2o early detection of disease (e.g. Pap

smear)

3o reduce disability from disease (e.g.

exogenous insulin for diabetics)

PDR: Prevent

Detect

Reduce disability

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Important prevention measures

(p.65)

Risk Factor Services

DiabetesYearly eye exam, weekly self foot exams,

urine tests for microalbuminemia

Drug Use Hepatitis immunizations, HIV, PPD for TB

AlcoholismInfluenza, pneumococcal immunization, PPD

for TB

Overweight Fasting blood sugar test for diabetes

Homeless, recent immigrant,

inmatePPD for TB

High-risk sexual behaviorTest for HIV, hepatitis B, syphilis, Gonorrhea,

Chlamydia

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Reportable diseases (p.65)

Only some infectious diseases are

reportable in ALL states

AIDS Chickenpox

Gonorrhea Hepatitis A and B

Measles Mumps

Rubella Salmonella

Shigella Syphilis

TB

Other diseases (including HIV) vary by

state

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Reportable diseases (p.65) Hep Hep Hep, Hooray, the SSSMMART

Chick is Gone! HepA

Hep B

Hep C

HIV

Salmonella

Shigella

Syphilis

Measles

Mumps AIDS

Rubella

TB

Chickenpox

Gonorrhea

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Leading causes of death in US by

age (p.66)

Infants

Congenital anomalies, short gestation/low birth weight,

SIDS, maternal complications of pregnancy, respiratory

distress syndrome

Age 1-14 Injuries, cancer, congenital anomalies, homicide, heartdisease

Age 15-24 Injuries, homicide, suicide, cancer, heart disease

Age 25-64 Cancer, heart disease, injuries, suicide, stroke

Age 65+Heart disease, cancer, stroke, COPD, pneumonia,

influenza

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Part 2: NUTRITION

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Basal Metabolic Rate

Metabolism of the body at rest

Heat production of the body when in astate of complete mental and physical

rest and in the post-absorptive state. BMR can be estimated at 20-25

Cal/kg/day

Varies between people and changes

throughout life. High when you are young, slows as you

age.

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Resting Energy Expenditure

Energy expended in the post-absorptivestate and is approx 10% higher thanBMR

Males: REE = 900 + 10W Females: REE = 700 + 7W Wis weight in kilograms

REE is then adjusted for physical activityby multiplying 1.2 for sedentary, 1.4 formoderately active, or 1.8 for very activeindividuals.

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Caloric Requirement

Age and Caloric requirements:

3 mo: 28 Cal/kg

9-12 mo: 6 Cal/kg

2-5 y/o: 2 Cal/kg

9-17 y/o: 1 Cal/kg

10% reduction in energy allowance for

adults > 50 y/o.

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Caloric Requirement

Unstressed hospitalized pts require 1.2

times their REE

Stressed, febrile, catabolic pts require

1.5-2 times their REE

Question 7 of 40

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A 79-year-old African-American female is admitted to the hospital for progressive shortness of breath. She

has no previous history of pulmonary insufficiency, and no history of emphysema, although she did smoke

one pack per day until she was 60. The symptoms started three weeks prior to admission, and were gradual

in onset. She has not had a cough, fever, or chest pain. She does have a history of hypertension, glaucoma,

arthritis, kidney stones, and hysterectomy. Medications at the time of admission include amlodipine,

ibuprofen, and eye drops. She is allergic to sulfur and penicillin, both of which caused a rash. Family history issignificant for colon cancer, breast cancer, arthritis, diabetes, and hypertension. Social history reveals that the

patient was married for forty years, but her husband died three months ago from heart failure. She lives

alone.

A chest x-ray at admission is suspicious for a mass in periphery of the left lower lung, and a follow up CAT

scan is suspicious for malignancy. Consultation is obtained from a pulmonologist, who performs a video

assisted thorascopic surgery (VATS) and biopsy. The pathology result reveals small cell carcinoma. An

oncologist is called for an opinion, and recommends chemotherapy since the tissue type indicates a good

chance of success. The problem is that the patient refuses treatment. She denies any depressive symptoms,

appears to be awake, alert, and oriented. She answers questions appropriately and does not appear to be

suffering from delirium or dementia.

As the patient's primary care physician, you would like to respect the patient's autonomy, but are concerned

about the consequences of her decision to forgo treatment. She has indicated to you that she understands

the proposed treatment options and that she understands how they relate to her situation. You decide to:

(A) Assess her competence by administering a bedside mental status examination

(B) Enlist the help of family members who may be able to change the patient's mind

(C) Respect her decision if she can demonstrate and communicate ability to reason

(D) Consult adult protective services because she is no longer able to care for herself

(E) Declare her incompetent and ask the oncologist to administer the chemotherapy

C Respect her decision if she can demonstrate and communicate ability to reason

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Competence is a legal term, capacity is a medical term. Physicians are often called on to make a determination of

a patient's capacity to make medical decisions. The patient's primary care provider is an ideal person to make

the assessment as they have background knowledge of the patient's educational level, values, and medical

history.

A psychiatrist may be needed if overlying psychiatric problems make it difficult to determine capacity for judgment

or ability to reason. Courts make the ultimate determination of competence, although there is usually

concordance with the medical determination of capacity. Only lack of competence has legal ramifications,

however.

A bedside mental status examination may help to determine capacity, but in and of itself does not determine

competence. If the patient is deemed to have the capacity to make her own decisions, it may be detrimental

to encourage family member involvement in the decision making process.

Adult protective services are usually called to investigate cases of abuse or neglect, not issues of capacity or

competence. If still unclear, a psychiatrist or ethics board consultation could be utilized to help determine the

patient's capacity to make her own decisions.

Four main criteria should be used to determine a patient's capacity to make medical decisions.

1) They can demonstrate understanding of the treatment options.

2) They can demonstrate understanding of how the different options affect their own individual situation.3) They can demonstrate ability to reason with the above information, using either evidence based in fact, or

personal beliefs rooted in their value system.

4) They are able to demonstrate 1-3 and can communicate a choice.

Question 37 of 40

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A 47-year-old male presents to his primary care physician complaining of markedly

increased feelings of stress secondary to recent changes at his workplace. Which ofthe following statements about stress and its health effects is true?

(A) Stress does not include emotionally negative responses such as anger and

hostility

(B) It is a factor in 10-20% of health problems

(C) Assertiveness training is unlikely to help an individual to avoid stress

(D) It is in the differential diagnosis for diarrhea

(E) It is the third leading cause of disability claims in California

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D It is in the differential diagnosis for diarrhea

The definition of stress is an individual's negative emotional response to

a perceived inability to meet demands place on him or her. It mayexpress itself as anger, hostility, or feelings of helplessness, loss of

control, or victimization. It is believed to be a factor in 60-80% of all

health problems, and is the leading cause of disability claims in

California. Major symptoms include fatigue, exhaustion, tight back and

shoulders, insomnia, anxiety, anger, headaches, depression, sadness,

hopelessness, colds, indigestion, diarrhea, and ulcer symptoms.

Effective prevention and avoidance techniques include assertiveness

training and the development of communication skills. Treatment

methods include relaxation techniques, meditation, exercise, andparticipation in enjoyable activities.

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Question 1 of 40

A 20-year-old man arrives at the emergency room asking for a strong pain killer

because he is in serious pain. The attending physician notices that he is veryanxious and is sweating. The man states that he has no appetite, he has a runny

nose, nausea, stomach cramps and diarrhea. He said that he took his temperature at

home at it was 100F. While he talks he is continuously yawning and restless. The

attending physician recognizes that he is abusing a certain substance and is

experiencing withdrawal. Which substance is it?

(A) Alcohol

(B) Cocaine

(C) Amphetamines

(D) Barbiturates

(E) Opioids

E Opioids

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The patient is experiencing the classic symptoms of withdrawal from opioids

which are anxiety, insomnia, anorexia, sweating, piloerection, fever, rhinorrhea,

nausea, stomach cramps, diarrhea, yawning. Symptoms usually appear within

8 to 10 hours after abstinence. The onset is longer if methadone has beenwithdrawn. These symptoms peak within 48 to 72 hours and then disappear in

7 to 10 days. Methadone lessens the effects of withdrawal. It should be given

no more than 20-50mg/day.

Alcohol withdrawal appears within a few hours of stopping or decreasing

alcohol consumption. It lasts for three to four days and sometimes as long as aweek. The patient experiences tachycardia, tremulousness, diaphoresis,

nausea, orthostatic hypotension, malaise, anxiety, and irritability.

Benzodiazepine should be administered in a tapering dose over three days.

Cocaine withdrawal is classified by psychological symptoms such as

increased sleep, REM rebound causing nightmares, lassitude, increased

appetite, depression, and suicide attempts. Treatment would consist of an

antidepressant such as bupropion. Amphetamine withdrawal would include a

post use crash, including anxiety, lethargy, headache, stomach cramps, hunger,

severe depression, dysphoria mood, fatigue, and insomnia or hypersomnia.

Barbiturate withdrawal is characterized by anxiety, seizures, delirium, and life

threatening cardiovascular collapse.

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Question 4 of 40

The city of Cancerville had a population of 10,000,000 (50% women) in

1995. In 1995, there were 80,000 women with previously diagnosedovarian cancer in Cancerville. Twenty thousand new cases of ovarian

cancer were diagnosed in 1995. What was the incidence rate of ovarian

cancer in Cancerville in 1995?

(A) 2000 per One hundred thousand population

(B) 4000 per One hundred thousand population

(C) 200 per One hundred thousand population

(D) 400 per One hundred thousand population

(E) 1,000 per One hundred thousand population

D 400 per One hundred thousand population

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D 400 per One hundred thousand population

The incidence rate is the number of new casesof a disease during a specific period per

population at risk. Twenty thousand divided by 5

million women gives a rate of 1 case per 250women, or 400 cases per One hundred thousand

populations.

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Question 8 of 40

A laboratory has developed a new test for rapid ascertainment

of serum parathyroid hormone levels. The test is repeatedtwenty times on the same sample with a resulting coefficient of

variation of one percent. This is a measure of

(A) Accuracy

(B) Reliability

(C) Precision

(D) Validity

(E) Mode

B Reliability

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-The mode is the most commonly occurring value in a series of

data.

-Reliability is a measure of the reproducibility of a test overdifferent conditions. The four most common types are inter-

observer reliability, intra-observer reliability, split-sample reliability,

and repeat testing reliability.

-Accuracy is a measure of the extent to which a test approximatesthe real value of that which is measured. New tests are measured

against the gold standard, if one exists.

-Validity is the assessment of the degree to which a test measures

that for which it was designed. In other words, you need to

determine whether it reflect the outcome of interest or otheroutcomes.

-Precision is the degree to which a measurement is not subject to

random variation.

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Question 10 of 40

At a large university, a study of pulse rates at rest was conducted

on 5000 students. The mean pulse rate was 70, with a standarddeviation of 10. Which of the following statements is true?

(A) Approximately 95% of the students had pulses between 60

and 80(B) Approximately 68% of the students had pulses between 60

and 80

(C) Approximately 99.7% of the students had pulses between 50

and 90

(D) Approximately 95% of the students had pulses between 40

and 100

(E) Approximately 68% of the students had pulses between 50

and 90

B Approximately 68% of the students had pulses

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pp y p

between 60 and 80

When a test is conducted on a normally distributedpopulation, 68% of the population will have values within

one standard deviation of the mean, 95% of the

population will have values within two standard

deviations of the mean, and 99.7% of the population willhave values within three standard deviations of the

mean. Therefore, in this population, 68% of the pulses

will be between 60 and 80, 95% between 50 and 90, and

99.7% between 40 and 100.

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Question 13 of 40

A statistician analyzes data for several academic departments. She is free to

choose the appropriate methodology to her perform her analyses. Which ofthe following data would best be analyzed by non-parametric statistical

methods?

(A) Results of a study on the effect of a new lipid-lowering drug on LDLcholesterol

(B) Results of a study on the effect of asbestos exposure on forced vital

capacity

(C) Results of a study on the relationship between gender and lung cancer

(D) Results of a study on the differences in weight distributions between

children in different countries

(E) Results of a study on the relationship between hemoglobin and

reticulocyte count

C Results of a study on the relationship between gender and lung cancer

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Parametric techniques can be used to analyze data where at least one of the

variables is quantitative (interval or ratio) and where the data is distributed

normally. If the data is not distributed normally or both variables are qualitative

(nominal or ordinal), non-parametric techniques must be used. Gender andlung cancer are both qualitative variables, so non-parametric techniques, such

as chi-square, are used to determine the relationship between them. LDL

cholesterol, forced vital capacity, hemoglobin, and reticulocyte count are

quantitative ratio variables, so studies involving them can be analyzed using

parametric techniques, assuming they are normally distributed. The use of anew lipid-lowering drug and the presence or absence of asbestos exposure is

qualitative nominal variables. Weight is a quantitative ratio variable, and various

parametric techniques can be used to compare the means, ranges, and

variances of distributions between populations.

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Question 15 of 40

You are doing a research project on comparing the effectiveness of

cognitive-behavioral versus psychoanalytic therapy in depressedpatients. Your subjects consist of 60 outpatient females being seen at the

local college clinic. They are randomly assigned to three groups: those

who will receive cognitive-behavioral therapy, those receiving

psychoanalytic therapy, and a third group that receives no therapy to

serve as a control group. In your study what is the independent variable?

(A) the subjects participating in the different therapy groups

(B) the therapies being compared in the study

(C) the subjects receiving no therapy

(D) the level of depression in the participants at the end of the study

(E) the assignment of the participants into the separate groups

B the therapies being compared in the study

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The independent variable is defined as the variable that is to be

manipulated or controlled, or that has been selected by theresearcher. In the study, as the researcher you are controlling the

type of therapy to be utilized in the study. You are also controlling

whether or not the participants are receiving any therapy at all.

The subjects that are participating in the different therapy groupsand that have been assigned to serve as the control group are the

sample being used in this study. The sample simply means the

participants chosen to represent the larger population. The level of

depression in the participants at the end of the study is considered

to be the dependent variable. The dependent variable is definedas the response to the independent variable (or therapy), the

observed or measured behavior, or the outcome of the study.

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Question 21 of 40

You are doing a study on the distribution of IQ scores in 15-year-old

adolescent males in a standard high school classroom. You have chosenone school from Los Angeles, Seattle, Dallas, Miami, Chicago and New

York. The WISC-III is administered to all 15-year-olds in the schools

selected. After all tests have been administered, the scores are collected

and the distribution of the scores is analyzed. The IQ scores represent what

type of statistical measurement scale?

(A) Nominal

(B) Ordinal

(C) Interval

(D) Ratio

(E) Correlational

C interval

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In statistical measurements, IQ is considered an interval scale because the

difference between an IQ of 90 and 100 is indistinguishable from the difference

in an IQ of 100 and 110. In interval scales, the difference between intervals is

relative. The difference between 1 and 2 is relative to the difference between 3and 4. Nominal measurements are used for variables in which there are no

numerical values that can be compared, such as gender or ethnic background.

Ordinal scales are used for rank ordering. Ordinal scales can be used for such

variables as attractiveness, or grades in school. In each case one can state that

s/he is more attractive then, or an A or B is better than a C or D. Ratio scalesare based in measurements where there is an absolute 0. In IQ's there are no

absolute zeros, and one cannot state that an IQ of 50 is half as good as an IQ

of 100. Ratio scales can be used for variables such as the number of hours a

student spends studying, 2 hours of studying would be half as many hours as 4

hours of study. Correlations are not used as a method of statisticalmeasurements, but are used in research and statistics to define a relationship

between two variables.

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Question 24 of 40

A researcher studied the levels of serum calcium in the U.S.

and Panama. The null hypothesis was proven. What does thenull hypothesis state?

(A) There is a significant difference between populations tested(B) Difference between populations is not attributable to chance

(C) Difference between populations is due to a particular factor

(D) There is no significant difference between populations

tested

(E) Power of a study to detect a significant difference between

populations is nil

D There is no significant difference between

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populations tested

The null hypothesis states that there is no significantdifference between the populations being tested, and

that any difference that is found is attributable to chance.

It is tested against the alternative hypothesis, which is

that there is a significant difference between thepopulations tested.

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Question 29 of 40

The public health officials of a particular city wish to evaluate the lead levels

of its constituents. In order to develop a sample population, they chooseevery 10th family in the city for the study. This is an example of what kind of

population sample?

(A) Stratified selected sample(B) Cluster selected sample

(C) Simple random sample

(D) Systematically selected sample

(E) Nonrandom selected sample

B Cluster selected sample

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In cluster selected samples, the population of interested is

divided into subunits, such as families, and a random sample of

these units is used.In simple random samples, each individual member of a

population has an equal probability of being chosen.

In stratified selected samples, individuals are chosen randomly

from within stratified groups, such as age groups.In systematically selected samples, the population is ordered

by some characteristic, such as age, a starting point for selection

is randomly selected, and then the remainder of the sample is

collected by a predetermined scheme, such as choosing every x

number of people.In nonrandom selected samples, some predetermined scheme

is used, such as the first x number of people presenting for a

certain disease to a clinic.

Q i 31 f 40

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A physician wants to learn more about prevalence rates for diabetes

mellitus in his local community. He has raw data from his town publichealth department, but he is not sure how to determine the prevalence

rates. Which of the following comments is true of prevalence rates?

(A) Reflect a portion of specific illnesses in a population(B) Include new and existing cases during a specific time period in the

numerator

(C) Denominator is the entire population, both those at risk and those not at

risk

(D) Include only cases prevalent at the start of the time period in the

numerator

(E) Are not influenced by the duration of disease

Question 31 of 40

B Include new and existing cases during a specific time

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period in the numerator

Prevalence rates are determined as the number of new

and existing cases of disease during a specific time

period in the numerator divided by the population at risk

in the denominator. They are influenced by both theduration of disease and the incidence of new cases. By

measuring both existent and new cases of illness, they

reflect the total amount of specific illnesses in a specific

population.

Q ti 36 f 40

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Question 36 of 40

You are conducting an experiment on the effectiveness of behavioral therapy in

treating social anxiety. Your research hypothesis is that behavioral therapy is

effective in reducing social anxiety. The participant's in your study are 30

individuals who have been diagnosed with social anxiety. Each individual is

independently evaluated for social anxiety to confirm the diagnosis. After the

evaluation, 6 participants are found to not meet the set criteria for social anxiety

and are dropped from the study. The remaining 24 participant's are broken up into

two separate groups. Group A receives behavioral therapy and group B is put ona wait-list to receive therapy after the experiment is over. At the end of the

experiment, you find that behavioral therapy was effective in treating social

anxiety. In your study what is the independent variable?

(A) The subjects participating in the treatment group

(B) The treatment administered to group A

(C) The subjects in the no treatment group

(D) The level of social anxiety in the participants at the end of the study

(E) The assignment of the participants into the separate groups

B The treatment administered to group A

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The independent variable is defined as the variable that is to be

manipulated or controlled, or that has been selected by theresearcher. In this study, as the researcher, you are controlling

whether or not participants receive therapy. The subjects that are

participating in therapy and those that have been assigned to

serve as the control group are the sample being used in thisstudy. The sample simply means the participants chosen to

represent the larger population. The level of social anxiety in the

participants at the end of the study is considered to be the

dependent variable. The dependent variable is defined as the

response to the independent variable (or therapy), the observedor measured behavior, or the outcome of the study.

Q ti 40 f 40

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Question 40 of 40

A researcher studied the relationship between childhood exposure to lead

and stature. The heights of the children measured at age 12 range from 4'8"to 5'9", with a standard deviation of 5", a mean of 5'3", a mode of 5'2", and a

coefficient of variation of 7.9%. Which of the following statements is true?

(A) Variance is the square root of the standard deviation(B) Range of a series of data provides information about the distribution of

the data

(C) Coefficient of variation is a measure of the spread of the data in regard

to the mean

(D) Standard deviation is an estimate of the standard error of a population

(E) Mode is a measure of central tendency of a data series

C Coefficient of variation is a measure of the spread of the data

in regard to the mean

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in regard to the mean

The coefficient of variation is defined as the standard deviation

divided by the mean, expressed as a percentage. It is a measureof the spread of the data with regard to the mean.

The standard deviation is the positive square root of the

variance.

The standard erroris an estimate of the standard deviation of apopulation.

The range of a series of a data is calculated as the highest value

in the series minus the lowest value, and it provides no

information about the distribution of data within the series.

The mode is the most commonly occurring value in a data seriesand does not provide any information about the central tendency

of a data series.

Question 2 of 40

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A researcher is preparing a paper for publication on characteristics of

hepatitis C infection in her local population. It includes exposure andtreatment information. She reports that female sexual partners of men with

hepatitis C virus are twice as likely than other women in the same population

to contract the hepatitis C virus. This is a measure of

(A) Type I (alpha) error

(B) Odds ratio

(C) Prevalence

(D) Attributable risk

(E) Bias

D Attributable risk

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Attributable risk, which can be determined from cohort studies, is

a measure of the difference in occurrence of disease between

exposed and unexposed populations. The likelihood that apositive result is due to chance is a measure of type I (alpha)

error.

Prevalence is the amount of disease existing in a population at acertain point in time.

The odd ratio is a measure of the estimated relative risk occurring

due to certain factors. Confounding variables may cause bias in

studies.

Question 6 of 40

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In reporting the results from a clinical study of a new anti-inflammatory drug for the

treatment of post-operative pain, the study's authors present data comparing the

total days of hospitalization for comparable groups of patients who have received

either the investigative anti-inflammatory drug or a placebo. The attached table

appears in their report. Which of the following would be a valid interpretation of the

data presented in this table?

(A) The p-value is greater than 0.05, indicating that there is no true treatment effect upon total days of post-operativehospitalization

(B) The treatment group and placebo groups have unequal numbers of participants, and therefore the statistical test

results are not interpretable

(C) The results are suggestive of a true treatment effect, but the study has limited power to detect the effect due to

the relatively small number of study subjects

(D) Statistical testing of two group means yields a t-value, not a p-value

C The results are suggestive of a true treatment effect, but the study haslimited power to detect the effect due to the relatively small number of study

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p y y

subjects

While the p-value for the differences between the mean days of post-operative

hospitalization is not below the conventional level of 0.05, it is relatively close tothat value. The values of the treatment group and placebo group means (3.0

and 4.5 days, respectively) do suggest that there is an effect of treatment. It is

likely that the statistical power of the study is rather limited, given the modest

number of people enrolled in each group. Ideally, this study would be repeated

with larger numbers of study subjects in each of the two groups. While it wouldbe a mistake to conclude that there was definitively a treatment effect, it would

also be a mistake to conclude that there was no evidence for a treatment effect,

as well.

In clinical trials, it is not necessary that the comparison groups have identical

numbers of subjects, although there should be a sufficient number of

participants in each study group to effectively evaluate the treatment being

considered. While statistical testing of two group means may use the t-test, it is

possible to derive a p-value from the use of this test.

Question 9 of 40

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Suppose that a researcher is using hypothesis testing to determine whether two

treatments are equally effective. The hypotheses being tested are given below.

H0: Treatment A and Treatment B are equally effective

Ha: Treatment B is more effective than Treatment A

The study used an a-level ofa = 0.05. The power of the test was 0.80. What is the

probability that H0 will be rejected if in fact the two treatments are equally effective?

(A) 0.05

(B) 0.20

(C) 0.80

(D) 0.95

(E) It is impossible to tell from the information given

A 0.05

Wh h h th i t ti th h b t i th t th l i h / h d

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When a researcher uses hypothesis testing, the researcher can never be certain that the conclusion he/she draws

is correct. The decisions a researcher makes versus the truth can be portrayed by the following table.

TRUTH

Ho

True Ha

True

RESEARCHER

ACCEPTS HoCorrect Decision

Type II Error

(Probability b)

RESEARCHER

ACCEPTS Ha

Type II Error

(Probability a)Correct Decision

If H0 is true, but by chance the data suggested strong enough evidence against H0 to reject H0, then a type IError has been committed. The probability of a Type I Error is the a-level of the test. Therefore, ifa = 0.01, then

only 1% of the time will data be strong enough to reject H0 when H0 is true, resulting in a Type I Error.

If Ha is true, but the evidence against H0 was not strong enough to reject H0, then a Type II Error has been

committed. The power of a test is defined as the probability of rejecting H0 when Ha is in fact true (the ability of

the test to correctly identify a significant difference). The power of a test is directly related to the probability of

committing a Type II Error. The probability of a Type II Error is b and the power of a test is given by (1 - b). One of

the most common reasons for a Type II Error is due to sample size being too small. In general, the larger thesample size, the greater the power of the test.

Question 11 of 40

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A trial is carried out to determine the impact of a new diet combined with exercise in addition to conventional therapy to further

reduce the risk of dying in patients recovering from heart surgery. Patients are assigned to one of the two study arms:

1- Conventional therapy only

2- Conventional therapy plus new diet plus new exercise program.

Patients are followed up every two months for the first year and then every six months for the next four years. Among other

factors, the following information is collected:

1) Sex

2) Age at time of surgery

3) Weight (at entry into trial and at each visit)

4) Percentage of body fat (at entry and at each visit)

5) Survival status and date of death where applicable

6) Need for further surgery and date where applicable

7) A grading for actual activity level (1 to 5 with 1=Sedentary & 5=Very Active)

Refer to the attached trial description. What study design is this?

(A) Case-Control study

(B) Cohort Study

(C) Randomized Clinical Trial

(D) Cross Over Study

(E) Cross Sectional

C Randomized Clinical Trial

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Two study arms are present. In the first one, only the conventional therapy is

present. In the second, diet and exercise are added to conventional therapy.

This is, therefore, an experimental study. The patients are assigned to only one

of the two study arms. Due to the nature of the intervention (diet plus exercise),patients are unblinded to their study group. This is a Randomized Clinical Trial.

In a cross-over study, patients are assigned to one of the study arms for a

period of time and then assigned to the other study arm for the same length of

time.

The other study designs mentioned are all observational studies. In case-control studies, people with and without a specific outcome are chosen. Then,

looking backward in time, one tries to detect possible causes or risk factors. In

cross sectional studies, data is collected at one time. Large governments

surveys are good examples of cross sectional studies. In a cohort study, people

are selected and followed over a period of time. At the beginning of the study,

people are defined as being exposed or not exposed to certain risk factors.

They are observed over time for the development of outcome. The outcome is

then compared to exposure to risk factors.

Question 14 of 40

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A researcher wishes to compare the efficacy of a COX-2 inhibitor to that of

ibuprofen for treatment of pain in patients with osteoarthritis. Using a visualanalogue scale of 1-100, a difference of 15 points between the mean values

of the treatment arms is considered to be clinically significant. Given that a

true clinically relevant difference exists between the two therapies, which of

the following is most true about the probability that the statistical test used in

the study will fail to detect the difference?

(A) The probability decreases as a decreases

(B) The probability is determined by the type-II error of the study

(C) The probability decreases as the b increases

(D) The probability is impossible to determine without knowing the true

mean

(E) The probability decreases as the power decreases

B The probability is determined by the type-II error of the study

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Before a study is conducted, the researcher must select the significance level

(a), which is the value used to interpret the result of the statistical test. The a

level represents the probability that the statistical test used will detect a

clinically significant difference due to chance alone. This is the chance of atype-I error. The a level does not predict the response of an individual patient,

or the proportion of a sample that will have a particular therapeutic outcome.

The probability of a statistical test failing to detect a difference between means

of two samples when such a difference truly exists, is the b or type-II error. Asthe level of significance increases, there is a greater chance of a type-I error,

but less chance of a type II error, therefore, b decreases as a increases.

The ability of a statistical test to detect a difference between two means is the

power of the test. Power is the probability that a statistical test will detect a

difference when such a difference truly exists and is not due to chance. Power

is the complement of b, and is equal to 1-b. Therefore, b decreases as power

increases. As the level of significance, and the chance of a type-I error

decreases, b increases. Power differs from a and b in that it is not a measure of

error.

Question 17 of 40

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In a study of the effects of a new treatment for ovarian cancer

on mortality, the a level is 0.05 and the b level is 0.20. What isthe power of the study to detect a change in mortality from this

new treatment?

(A) 5%

(B) 20%

(C) 25%

(D) 80%

(E) 95%

D 80%

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The power of a study is the ability of the study to detect

a significant change when one exists. It is calculated as1 - b, where b is the Type II error. In this case, 1 - b =

0.80, or 80%. Therefore, there is an 80% surety that this

study has detected a change in mortality with this new

treatment when one exists. Or, in other words, 20% ofthe time it will have missed a significant difference when

one exists.

Question 20 of 40

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You and your colleagues are conducting a small clinical trial concerning the

management of pediatric asthma. The clinical trial involves three differenttreatment arms and one placebo arm. The outcome of interest is

hospitalization for respiratory distress. In one treatment arm (n=31), there

are no patients that require hospitalization during the follow-up period (i.e., 0

events). What is the upper 95% confidence bound for the rate of

hospitalization for the 31 subjects in this treatment arm?

(A) The upper 95% confidence bound cannot be calculated from the data

provided

(B) 0(C) 0.10

(D) 0.15

(E) 0.22

C 0.10

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The answer to this question is derived using the "rule of three" (as

explained by Hanley and Hand, JAMA, 1983). When there are no

events of interest observed in a particular group, the upper 95%confidence bound can be calculated by dividing 3 by the number

of subjects in the group (i.e., n). In the question, 3/n is equivalent

to 3/31 or 0.097. Rounding up produces the answer 0.10, and

thus the largest rate that we would expect (with 95% confidence)

would be 0.10 or approximately 3.0 events in this group of 31

study subjects. The 99% confidence bound can be obtained by

using the "rule of 4.6" (i.e., 4.6/n), and the 99.9% confidence

bound can be obtained using the "rule of 6.9" (i.e., 6.9/n). While

this explanation will not go into the derivation of this rule, thecalculations underpinning the convenient statistical device are

sound and well-tested.

Question 32 of 40

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During a research rotation as a medical student, you spend several months

gathering data on the use of a new oral vaccine to prevent a serious gastrointestinal

disease in primates. Your research generates the attached table of data, and you are

interested in using the c2 test to statistically test the association between vaccination

status and the subsequent development of this particular gastrointestinal disease.

After calculating the c2 value, you are interested in looking at a table ofc2 values to

determine the p-value that is associated with the c2 value that you obtained with the

numbers shown in the table above. What would be the correct "degrees of freedom"

associated with this table

(A) 1 degree of freedom

(B) 2 degrees of freedom

(C) 3 degrees of freedom

(D) 4 degrees of freedom

(E) 5 degrees of freedom

A 1 degree of freedom

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The shape of the c2 distribution changes according to the number

of degrees of freedom (df) involved in a particular testing situation.

Thus, in order to determine the correct p-value associated with aparticular c2 value, it is necessary to know the correct degrees of

freedom. For contingency tables, the correct degrees of freedom

is obtained with the following formula: df= (r-1)(c-1), where ris the

number of rows, and cis the number of columns. In a table with 2

rows and 2 columns, the c2 test will have 1 degree of freedom.

Question 36 of 40

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While doing morning rounds on the pediatric bone marrow transplantation

unit at a large university-affiliated medical center, the attendinghematologist-oncologist asks you about the allocation of patients to

treatment groups in pediatric marrow transplantation clinical trials. How

should you answer her question most correctly?

(A) Patients are allocated based on prognosis

(B) Patients are allocated based on parental preference

(C) Patients are allocated by random assignment

(D) Patients are allocated based on the attending physician's clinical

judgment

(E) Clinical trials cannot be done with pediatric subjects

C Patients are allocated by random assignment

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To effectively evaluate experimental agents or

procedures, randomized clinical trials must be

performed. Randomized clinical trials should be double-blinded in all but the most exceptional circumstances,

and patient allocation should be achieved by a random

process in which each patient has the same probability

of being allocated to a specific treatment or control arm.

Allocation based on prognosis, parental preference, or

clinical judgment can lead to seriously biased results

and flawed conclusions about the efficacy of theexperimental treatment.