Soc. 2155 Week 3 Causation and Experiments

I. Causation– Relationships between variables– Types of association– Criteria for causality

II. Experiments – testing cause and effect– Explanatory research– True experimental designs– Quasi-experimental designs– Internal validity– External validity– Ethical issues– Strengths and weaknesses

Association = relationship• Does not have to be causal.

• Positive association = as X increases, Y increases.

• Negative association = as X increases, Y decreases.

• Qualitative variables: presence of X predicts presence or absence of Y.

Which associations could be causal?

• Years work experience/ income

• # churches / # bars in a town

• Cigarette smoking/ lung cancer

• # firefighters called to fire/ $ amount of damage

• Race/ poverty

Spurious association = apparent association caused by a third factor

Cause = necessary and sufficient condition

Necessary: X must be present in order for Y to follow.

(ex: to get an “A” it is necessary to complete all assignments).

Sufficient: If X occurs, Y must follow.(ex: if you get 100% on every assignment, you will get an

“A” in the class.)

3 criteria for causalityX causes Y if:

• X precedes Y in time

• X and Y are statistically associated

• All other potential causes of Y have been ruled out.

Additional Criteria

• Mechanism – connection between “cause” and “effect” – how the cause operates to produce the effect.

• Context – situations, groups, places, conditions, etc. In which the cause produces the effect.

Determinants/ partial causesMost sociological phenomena have multiple

causes. “Determinant” = partial cause or predictor. Not a complete cause.

Example: Some determinants of income:

Education

Skill

Training

Experience

Intelligence

Marital status

Talent

Personality

Job duties

Type of company

Occupation

Gender

Race

Geographic area

Industry

Types of Causes

Nomothetic Cause – General explanation of a class of phenomena. (e.g., causes of terrorism, crime)

Idiographic Cause – Specific event or sequence of events. (e.g., causes of 9/11 attacks, sudden rise in crime rates) May be historical in focus.

Multivariate Relationships

ZX

Y

Y

Y

Y

Z

Z

Z

XX

X

Multiple causes (determinants) of Y

Z as spurious cause of X and Y

Direct and indirect effects

Z intervenes B/T X and Y OR Z “explains” relationship B/T X and Y

Experiments

• Explanatory research• True experiments• Experimental designs• Quasi-experimental designs• Internal validity• External validity• Ethical issues• Strengths and weaknesses

Explanatory Research

• Purpose: to explain, to determine cause/effect

• What is explained? Variation in the dependent variable

• What can be studied in an experiment?Limited, narrow causal relationships

Variables that can be studied in lab

Topics for which theory has been developed

True experiment includes

• Two groups (experimental and control)

• Random assignment to groups

• Variation in independent variable (manipulated by researcher)

• Measurement of dependent variable

The groups

• Experimental group – is exposed to independent variable (I.V.)

• Control group - is not exposed to I.V.

• I.V. is the only difference between the groups

• Any differences in dependent variable (D.V.) must be due to I.V.

Assignment to groups

• Randomization

– Easy to carry out

– Can control for unmeasured or uncontrolled factors

• Matching

– Specific characteristics matched in both groups

– May be very precise

– Requires knowledge of relevant characteristics

– May not control for omitted factors

Pretesting

• Measures D.V. before experiment

• Establishes comparability of experimental and control groups

• Provides baseline for comparison with posttest

• May teach or “clue in” subjects (pretest effect)

• Costs extra

Experimental Designs

Effect of I.V. = (O3-O1) – (O4-O2)

Groups Pretest I.V. Uncontrolled factors

Posttest Change

Exper. O1 X X O3 O3-O1

Control O2 X O4 O4-O2

Classic Pretest-Posttest-Control-Group

Experimental Designs

Effect of I.V. = (O1-O2)

Eliminates effect of pretest

Groups Pretest I.V. Uncontrolled factors

Posttest Change

Exper. N/A X X O1 N/A

Control N/A X O2 N/A

Posttest-Only

Experimental Designs

Effect of I.V. = (O3-O1) – (O4-O2) or (O5-O6)

Effect of pretest = (O3-O5) or (O4-O6)

Groups Pretest I.V. Uncontrolled factors

Posttest Change

Exper. 1 O1 X X O3 O3-O1

Control 1 O2 X O4 O4-O2

Exper. 2 X X O5

Control 2 X O6

Solomon four-group

Quasi-Experimental Designs

• May be used when true experiment isn’t possible

• Usually involve fewer controls– No control group– Approximately equivalent control group– May take place in the field– May be “ex post facto:” designed after the

“treatment”

Internal ValiditySource of Invalidity Solution

History – outside events Control group

Maturation – changes in subjects Control group

Testing – subject may learn Control group

Instrumentation - measurement Control group

Statistical regression - moderation Control group

Selection bias- groups not comparable Randomization

Mortality – dropping out Randomization

Contamination (competition, demoralization) Randomization

Treatment misidentification (experimenter expectations, placebo effect, Hawthorne effect)

Randomization, double blind, process analysis

External Validity

• Generalization to “real world”

• Often a problem in experiments

• 2 main issues– Would sample subjects behave same way

outside lab?– Cross-population generalizability: would

findings hold for different groups, times, places?

Ethical Issues

• Deception (misleading subjects about purpose of experiment)

• Selective distribution of benefits (also risks, harm)

Experiments’ Strengths and Weaknesses

Strengths

Isolation of cause/effect

High internal validity

Easy to replicate

Best used for explanatory studies (testing of hypotheses)

Weaknesses

External validity may be low or undetermined

Ethical issues

High cost per subject