Descriptive Methods◦ Observation◦ Survey Research

Experimental Methods◦ Independent Groups Designs◦ Repeated Measures Designs◦ Complex Designs

Applied Research◦ Single-Case Designs and Small-n Research

◦ Quasi-Experimental Designs and Program Evaluation

PSYCHOLOGICAL EXPERIMENTS

LOGIC OF EXPERIMENTAL RESEARCH

RANDOM GROUPS DESIGN◦ Block Randomization

◦ Threats to Internal Validity

ANALYSIS AND INTERPRETATION OF EXPERIMENTAL FINDINGS◦ The Role of Data Analysis in Experiments

◦ Describing the Results

◦ Confirming What the Results Reveal

◦ What Data Analysis Can’t Tell Us

ESTABLISHING THE EXTERNAL VALIDITY OF EXPERIMENTAL FINDINGS

MATCHED GROUPS DESIGN

NATURAL GROUPS DESIGN

Independent Groups Designs

Experiments:

◦ Empirical testing of hypotheses

◦ Testing contemporary theories

◦ Identification of the causes of behavior

◦ Testing intervention

Manipulation◦ IV on DV to observe the effect on behavior

Experimental control◦ causal inference (IV caused the observed changes in the DV)◦ Control is an essential ingredient◦ gained through manipulation, holding conditions constant,

and balancing Causal Inferences (three conditions)

◦ covariation, time-order relationship, and elimination of plausible alternative causes.

When confounding occurs, a plausible alternative explanation for the observed covariation exists, and therefore, the experiment lacks internal validity. Plausible alternative explanations are ruled out by holding conditions constant and balancing

Each group of subjects participates in only one condition of

IV

Comparable groups

◦ Manipulation: Random assignment of conditions

◦ Holding Conditions Constant

◦ Balancing or averaging subject characteristics (individual differences)

◦ independent groups for the levels of the independent variable Dittmar et al. (2006)

◦ Barbie,Emme, neutral

Intact groups:

◦ Potential confounding due to preexisting differences

Balancing Extraneous Variables

◦ Experimenter, observer

Selective subject loss > Mechanical subject loss

Demand characteristics

Placebo control groups

Double-blind experiments

Good research question Good experiment

Role of Data Analysis in Experiments

Statistics as Principled Argument (1995) by Robert Abelson

◦ “primary goal of data analysis is to determine whether observations

support a claim about behavior”

Replication Reliability

Data analysis and statistics Alternative to replication

Descriptive statistics that

◦ Mean (central tendency)

◦ Standard deviation (variation/individual differences)

Measures of effect size

◦ strength of the relationship and they are not affected by sample size.

◦ Cohen’s’ d: More than mean difference

◦ difference between two group means relative to the average variability

◦ small, medium, and large effects (.20, .50, and .80)

Meta-analysis

◦ Measures of effect size to summarize the results of many experiments

investigating the same independent variable or dependent variable

Inferential statistics◦ Reliable effect of IV on DV?◦ To infer results of sample on population◦ Difference due to chance (error variance)

Two methods (Null hypothesis testing and confidence intervals)

NHST◦ Probability theory whether difference is due to error variance◦ T-test, F-test etc.◦ A statistically significant = small likelihood of occurring if the null

hypothesis < 5% confidence intervals

◦ Probability of CI (.95)◦ Width of interval (the narrower the better)◦ Degree of overlap reliable difference of sample means

Results of study have practical value or even

if they are meaningful?

No certainty regarding conclusion

Errors:

◦ A Type I error: is like a false alarm—saying that

there is a fire when there is not

◦ Type II error: we have insufficient evidence to reject

the null hypothesis and it is, in fact, false

External validity

◦ Application to other individuals, settings, and conditions

Theory-testing

Emphasis on internal validity over external validity

Field experiments increase the external validity

Partial replication external validity

Generalization of conceptual relationships

A matched groups design

◦ Too few subjects available for random assignment to work effectively

Matching

◦ Best on the dependent variable tasks

After matching task

◦ Random assignment to the conditions

Individual differences variables (or subject variables) are selected rather than manipulated to form natural groups designs.

The natural groups design represents a type of correlational research in which researchers look for covariations between natural groups variables and dependent variables.

Causal inferences cannot be made regarding the effects of natural groups variables because plausible alternative explanations for group differences exist.