descriptive methods ◦ observation ◦ survey research experimental methods ◦ independent groups...
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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.