Independent Variables in Experimental Design Manipulations and Manipulation Checks Moderator vs. Mediator

Causal research

Experiments Studies in which conditions are controlled so that one or more independent variable(s) can be manipulated to test a hypothesis about a dependent variable Manipulation of A treatment variable (x), followed by observation of response variable (y) Experiment must be designed to control for other variables to establish causal relationship

Types of Evidence That Supports a Causal Inference Concomitant variation--evidence of the extent to which X and Y occur together or vary together in the way predicted by the hypothesis Time order of occurrence of variables--evidence that shows X occurs before Y Elimination of other possible causal factors—evidence that allows the elimination of factors other than X as the cause of Y X -- the presumed cause Y -- the presumed effect

Conceptualizing the Independent Variable Operationalization Select a particular way of manipulating the conceptual variable Generalization through systematic replication Manipulating the independent variable in different ways

Conceptualizing the Independent Variable (Cont.) Direct manipulations S -> R Inducing internal states S -> (R -> S) -> R

Example: Mood and Emotion Manipulations Movies Sophie‘s Choice, Ordinary People Pretty Woman, Mrs. Doubtfire Recalling past experiences Music Ein Musikalischer Spass – Mozart Adagio for Strings - Barber Associated nonverbal approach / avoid behaviors

Decisions What operationalization should be used? How can the impact of the manipulation be maximized? How to check whether the manipulation was effective?

Types of Manipulations Instructions Attention Understanding Task requires understanding Give test of understanding Keep it simple

Types of Manipulations Instructions Can be used to induce different mental sets and processing Example: Memory vs. Impression set Hamilton, Katz, & Leirer Better memory for traits when asked to form impression of person than to merely remember them Induce different motivations Example: Test of ability vs. game

Events Accidents Helping studies Induced compliance dropping pencils smoke-filled room Induced compliance

Controling for Demand Characteristics Pacebo effects Expectations must be controlled for “Good” subjects Attempt to behave consistent with the presumed hypothesis “Bad” subjects Attempt to behave contrary with the presumed hypothesis Hide purpose of the study

Pretesting Prior to experiment Examine effectiveness of a manipulation Materials understandable? Levels of variable are appropriate? Measurements valid & reliable?

Manipulation Checks Measures to ensure manipulation was effective during actual experiment Explicit Implicit Best placed immediately after manipulation, although not always possible

Controlling Experimenter Influence Naive experimenters Blind to condition / Double-blind Automated instructions Running conditions simultaneously Partially blind (unaware of one variable)

Participant Variables/Individual Differences Cannot infer causality when the independent variable is not manipulated Individual differences can complete a model of behavior Can also remove error variance and make effects of independent variable more clear Many individual differences can also be situationally manipulated

Moderation vs. Mediation Baron & Kenny (1986). The Moderator-Mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182 What are the differences between moderation and mediation? Are the interchangeable terms?

Moderation Moderation: A moderator is a qualitative (e.g., sex, race, SES) or quantitative (e.g., motivation) variable that affects the direction and/or strength of the relation between an independent/predictor variable and a dependent/criterion variable. A moderator variable partitions a focal independent variable into subgroups that establish its domain of maximal effectiveness with respect to a particular dependent variable. What other statistical concept does this sound like?

Mediation Mediation: A given variable may be said to function as a mediator to the extent that it accounts for the relationship between an IV and a DV A mediator variable represents the generative mechanism through which the focal independent variable is able to influence the particular DV of interest. Whereas moderator variables specify when certain effects will hold, mediators speak to how or why such effects occur.

A variable that changes the impact of one variable on another. Moderator A variable that changes the impact of one variable on another. Predictor Outcome Moderator

Testing a Moderator Hypothesis

Don’t Presume Linearity

The mechanism by which one variable affects another variable Mediator The mechanism by which one variable affects another variable

Testing Mediation Step 1: IV DV Step 2: IV Mediator Step 3: Mediator DV Step 4: Effect of IV on DV is significantly reduced by controlling for the mediator: Sobel (1982) test (http://www.unc.edu/~preacher/sobel/sobel.htm) Goodman (1960) test On the exact variance of products. Journal of the American Statistical Association, 55, 708-713.