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| A research procedure in which some factor is varied, all else is held constant, and some result is measured. |
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| Joint Method of Agreement and Difference |
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| If two or more instances in which the phenomenon occurs have only one circumstance in common, while two or more instances in which it does not occur have nothing in common save the absence of that circumstance: the circumstance in which alone the two sets of instances differ, is the effect, or cause, or a necessary part of the cause, of the phenomenon. |
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| The factor of interest to the researcher; it can be directly manipulated by the experimenter or participants can be selected by virtue of their possessing certain attributes. |
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| Behavior measured as the outcome of an experiment. |
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| Occurs when scores on two or more conditions are at or near the maximum possible for the scale being used, giving the impression that no differences. |
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| Occurs when scores on two or more conditions are at or near the minimum possible for the scale being used, giving the impression that no differences exist between the conditions. |
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| A group not given a treatment that is being evaluated in a study; provides a means of comparison. |
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| A condition where no treatment is administered to create comparison. |
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| "Pre-made", already established groups. For example, all of the students enrolled in PSY 395 FS12. |
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| The most common procedure for creating equivalent groups in a between-subjects design; each individual volunteering for the study has an equal probability of being assigned to any one of the groups in the study. |
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| Used to accomplish random assigned and ensure an equal number of participants in each condition; ensures that each condition of the study has a subject randomly assigned to it before any condition has a subject assigned to it again. |
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A four part designed used when it is suspected that in taking a test more than once, earlier tests have an effect on later tests
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| If a score on a test is extremely high or low, a second score taken will be closer to the mean score; can be a threat to the internal validity of a study if a pretest score is extreme and the posttest score changes in the direction of the mean. |
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| A threat to the internal validity of a study; occurs when some historical event that could affect participants happens between the beginning of a study and its end. |
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| A threat to the internal validity of a study; occurs when participants change from the beginning to the end of the study simply as a result of maturational changes within them and not as a result of some independent variable. |
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| Occurs when participants' behavior is influenced by the knowledge that they are being observed and their behavior is being recorded in some fashion. |
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| If experimenters treat subjects differently in the different groups of the experiment in ways other than those required to implement the independent variable. |
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| Experimental Research Designs |
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Definition
Natural Groups Design
Randomized Groups Design/Between Subjects
Matched Groups Design
Repeated Measures Design/Within Subjects |
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| Participant/Subject Variable |
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| Individual Differences serve as IV; Cannot “assign” subjects; Subject-variable confounds; Difficult to draw causal inferences. |
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| A between subjects design that uses a manipulated independent variable and has at least two groups of participants; subjects are matched on some variable assumed to affect the outcome before being randomly assigned to the groups. |
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| Any experimental design in which the same participants serve in each of the different conditions of the study; also called a "repeated-measures design". |
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| Any experimental design in which different groups of participants serve in the different conditions of the study. |
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| Can occur in a within-subjects design when the experience of participating in one of the conditions of the study influences performance. |
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| For a within-subjects variable, any procedure designed to control for sequence effects. |
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Form of partial counterbalancing in which each condition of the study occurs equally often in each sequential position and each condition precedes and follows each other condition exactly one time
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| The extent to which the findings of a study generalize to other populations, other settings, and other times. |
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| Relational (Correlational) |
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| Research attempts to determine how to or more variables are related to each other. |
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| Cross Lagged Panel Correlational Procedure |
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Definition
If variables X and Y are measured at two different times. If X at Time 1 is correlated with Y at time 2 but Y at time 1 is not correlated with X at time 2 then X might cause Y, but Y probably does not cause X.
** Helps determine directionality, strengthen case for causality |
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| The extent to which a study is free from methodological flaws, especially confounding factors. |
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| A correlation that can be explained by a third variable. |
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The mechanism by which the focal independent variable affects the dependent variable of interest.
Full mediation and Partial Mediation |
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Step 1: Estimate the association between the IV & DV
Step 2: Estimate the association between the Mediator & IV
Step 3: Estimate the association between the mediator and the DV
Step 4: The association between the IV an DV must be reduced when the Mediator is accounted for. |
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| Regression gives best fit line through data in terms of predicting Y from X |
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| Total variability = residual variability + explained variability |
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| Coefficient of Determination |
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| For two correlated factors, the proportion of variance in one factor that can be attributed to the second factor; found by squaring Pearson's r. |
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| Limited variability in a population that leads to a diminished correlation. |
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| A multivariate analysis that includes a criterion variable and two or more predictor variables; the predictors will have different weights. |
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| In correlational research, this refers to the fact that for a correlation between variables X and Y, it is possibly that X is causing Y, but it is also possibly that Y is causing X; the correlation along provides no basis for deciding between the two alternatives |
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| Types of Independent Variables |
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Short for Analysis of Variance. The most common inferential statistical tool for analyzing the results of experiments when dependent variables are measured on interval or ratio scales.
Omnibus test
Tells IF there is an effect, not where. |
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Definition
If σ = σA = σB = σC then the best estimate of the population variance is the average of the sample variances:
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If μ = μs = μN = μA then the variability we see between the sample means of each condition is just a function of the population variance:
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| Any experimental design with more than one independent variable. |
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| Refers to whether or not statistically significant differences exist between the levels of an independent variable in a factorial design. |
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| In a factorial design, occurs when the effect of one independent variable depends on the level of another independent variable |
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| Different Patterns of Interaction |
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| Cross over, partial cross over, no cross over. |
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| Lines are parallel, never interact |
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| Depending on scale, lines may cross or not (ARE NOT PARALLEL - Some relationship exists) |
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| Statistical Interpretation of Effects in Factorial |
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| If you have significant cross over interaction, where the direction of the effect of one variable depends on the other variable, the main effects aren’t really meaningful. |
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| 8 Sets of Possible Effects - 2 Factor Design |
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Definition
1.Main effect for factor A
2.Main effect for factor B
3.Main effects for A and B only
4.Main effect for A plus an interaction
5.Main effect for B plus an interaction
6.Main effects for both A and B plus an interaction
7.An interaction only, no main effects
8.No main effects, no interaction |
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| Mixed P x E Factorial Design |
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Definition
| A factorial design with at least one between-subjects and one within-subjects factor |
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| A factorial design with at least one subect factor (P= person variable) and one manipulated factor (E=environmental variable) |
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| When a persuasive message (e.g., political ad) that is paired with a discounting cue (e.g., paid for by lobbyists) appears to gain credibility over time. |
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| Hypothesis Testing (Steps) |
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Definition
1. State your hypotheses in terms of means
2. Establish your alpha level, then specify your decision criteria using t scores.
3. Calculate the t score given the null hypothesis.
4. Make a decision and draw your conclusion. |
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| Rejecting the null hypothesis when it is true; finding a statistically significant effect when no true effect exists. |
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| Failing to reject the null hypothesis when it is false; failing to find a statistically significant effect when the effect truly exists. |
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| Problems with Hypothesis Testing |
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Definition
| Type I & II Errors, Optional Stopping, p-Hacking, Replication, p Values are Confusing, α is arbitrary |
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Definition
When a researcher does not fix the sample size a priori, but sets out to obtain a significant p value by using the following stopping rule:
“Continue testing additional subjects until |Z| > zcrit.” |
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Researchers have a lot of freedom in the studies they run.
- Should we collect more data?
- Should we exclude some observations?
- Which conditions should be combined and which ones compared? |
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