Chapter 7 of 87% of exam

Research Methods and Statistics

This domain covers sampling, research design, statistical analysis and interpretation, critical appraisal and program evaluation. Items are usually short and precise: a design, a statistic or a threat to validity.

Designs and validity

Design questions ask which design controls which threat to validity. Internal validity concerns causal conclusions within a study, and external validity concerns generalization. Single-case designs are included and tested by their structure.

Random assignment

Strengthens internal validity; how the sample is drawn governs external validity.

Shadish, Cook & Campbell (2002)

Regression toward the mean

Participants selected for extreme scores tend to score closer to the mean on retest.

Campbell & Stanley (1963)

Solomon four-group

Adds unpretested groups to detect pretest sensitization.

Solomon (1949)

Single-case designs

Multiple-baseline designs stagger an intervention across settings, behaviors or people without withdrawing it.

Baer, Wolf & Risley (1968)

Statistical decisions

Statistical decisions involve two kinds of error and the power to detect a real effect. Items ask what raises or lowers power and which test fits a given type of data. The level of measurement of the variables usually decides the test.

Type I and Type II errors

Type I rejects a true null (alpha); Type II fails to reject a false null.

Neyman & Pearson (1933)

Power

Increases with sample size, effect size, a more lenient alpha and a one-tailed test; decreases with error variance.

Cohen (1988)

Chi-square

Tests relationships between nominal variables using frequencies.

Pearson (1900)

Effect sizes and interpretation

The outline separates statistical significance from effect size and clinical meaning. Effect sizes put results on a common scale and can be computed from summary statistics. Correlation questions often turn on shared variance and on the limits of causal inference.

Cohen's d

Mean difference divided by the pooled SD; 0.20, 0.50 and 0.80 are conventional small, medium and large values.

Cohen (1988)

Shared variance

r squared gives the proportion of variance two variables share.

Standard statistics

Association vs causation

A correlation alone does not establish causation; design determines causal inference.

Shadish, Cook & Campbell (2002)

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