Summary of Research Designs for Quantitative

Studies

Types of Designs

•  Pre-experimental: Little or no control •  Experimental: High degree of control •  Quasi-experimental: Minor level of control because

random selection or assignment is not possible. Statistics is used to improve the control of variables

Pre-Experimental Designs

•  Case study •  One group pretest – posttest •  Static group comparison or

cross-sectional

•  Diagram: X O2 •  Description: One group is studied after applying a

treatment or intervention •  Threats to validity: Little or no control of the effect of

variables, history, maturation, selection, mortality, and interaction effects of selection biases and the experimental treatment

X = Treatment O2 = Posttest

Case Study Design

•  Diagram: O1 X O2

•  Description: The dependent variable is measured, the treatment or intervention is applied, and the dependent variable is measured again

•  Threats to validity: History, maturation, instrumentation, mortality, selection- maturation interaction, reactive effect of testing, and interaction effects of selection biases and the experimental treatment

One Group Pretest- Posttest Design

O1 = Pretest X = Treatment O2 = Posttest

•  Diagram: X O2

- O2 •  Description: A group to which a treatment has been

applied is compared to another group that has not experienced it

•  Threats to validity: Selection, mortality, reactive effect of testing, and interaction effects of selection biases and the experimental treatment

X = Treatment O2 = Posttest

Static Group Comparison or Cross- Sectional Design

Experimental Designs

•  Randomized posttest groups •  Pretest- posttest control group •  Solomon four groups •  Factorial

•  Diagram: R X O2

R - O2 •  Description: Two groups are compared using posttest

and random assignment of subjects and treatment to control prior differences

•  Threats to validity: The change of the experimental group cannot be measured

R = Randomization X = Treatment O2 = Posttest

Randomized Posttest Groups Design

•  Diagram: R O1 X O2

R O1 - O2 •  Description: Two groups are compared using pretest

and posttest and random assignment of subjects and treatment

•  Threats to validity: Reactive effect of testing

R = Randomization O1 = Pretest X = Treatment O2 = Posttest

Pretest –Posttest Control Group Design

•  Diagram: R O1 X O2

R O1 - O2  

R - X O2

R - - O2 •  Description: To address the reactive effect of testing,

two control groups are added to the pretest-posttest control group design; one without taking pretest and another one without pretest and treatment

•  Threats to validity: None by itself

R = Randomization O1 = Pretest X = Treatment O2 = Posttest

Solomon Four Groups Design

•  Diagram: R X11 O (Notation of a 2 X 2 factorial design) R X12 O  

R X21 O

R X22 O •  Description: The different levels of two or more independent

variables (factors) are considered to establish not only their effects on the dependent variable but also the ones caused by the interaction among them

•  Threats to validity: None by itself

R = Randomization X11 = Factor 1, level 1 X12 = Factor 1, level 2 X21 = Factor 2, level 1 X22 = Factor 2, level 2 O = Measurement

Factorial Design

Quasi-Experimental Designs

•  Nonrandomized pretest-posttest control group •  Counterbalanced •  Time series

•  Diagram: O1 X O2

O1 - O2 •  Description: Two groups are compared using pretest

and posttest. There is not random assignment of subjects since they are already in groups

•  Threats to validity: Selection, statistical regression, and reactive effect of testing

O1 = Pretest X = Treatment O2 = Posttest

Non Randomized Pretest –Posttest Control Group Design

•  Basic Diagram : Treatments XA XB G1 XA XB O  

G2 XB XA O

•  Description: The order in which treatments are administrated is

changed during the study so as to test every subject for all the considered conditions

•  Threats to validity: Multiple treatment interference

X = Treatment G = Group O = Measurement

Counterbalanced Design

•  Diagram : O1 O2 … X Oi… On

•  Description: The dependent variable is measured several times

before applying a treatment and then a new series of

measurement is performed

•  Threats to validity: History and reactive effect of testing

X = Treatment O = Measurement

Time Series Design