Experimental Research

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Presentation transcript:

Experimental Research

Experiments Begin with a Hypothesis Modify Something in a Situation Compare Outcomes Cases or People are Termed “Subjects”

Random Assignment Probability of Equal Selection Allows Accurate Prediction An Alternative to Random Assignment is Matching

Parts of the Classic Experiment Treatment or Independent Variable Dependent Variable Pretest Posttest Experimental Group Control Group Random Assignment

Variations on Experimental Design Pre-experimental Design One-shot Case Study One-group Pretest-Posttest Design Static Group Comparison Quasi-Experimental and Special Designs

Types of Validity External Validity Internal Validity Do the results apply to the broader population? Internal Validity Is the independent variable responsible for the observed changes in the dependent variable?

Confounding Variables That Threaten Internal Validity Maturation Changes due to normal growth or predictable changes History Changes due to an event that occurs during the study, which might have affects the results

Confounding Variables That Threaten Internal Validity Instrumentation Any change in the calibration of the measuring instrument over the course of the study Regression to the Mean Tendency for participants selected because of extreme scores to be less extreme on a retest Selection Any factor that creates groups that are not equal at the start of the study

Confounding Variables That Threaten Internal Validity Attrition Loss of participants during a study; are the participants who drop out different from those who continue? Diffusion of treatment Changes in participants” behavior in one condition because of information they obtained about the procedures in other conditions

Subject Effects Participants are not passive They try to understand the study to help them to know what they “should do” This behavior termed “subject effects” Participants respond to subtle cues about what is expected (termed “demand characteristics”) Placebo effect: treatment effect that is due to expectations that the treatment will work

Experimenter Effects Any preconceived idea of the researcher about how the experiment should turn out Compensatory effects

Types of Control Procedures General control procedures (applicable to virtually all research) Control over subject and experimenter effects Control through the selection and assignment of participants Control through specific experimental design

Principles of Experimental Design Control the effects of lurking variables on the response, most simply by comparing two or more treatments Randomize Replicate

Randomization The use of chance to divide experimental units into groups is called randomization. Comparison of effects of several treatments is valid only when all treatments are applied to similar groups of experimental units.

How to randomize? Flip a coin or draw numbers out of a hat Use a random number table Use a statistical software package or program Minitab www.whfreeman.com/ips

Statistical Significance An observed effect so large that it would rarely occur by chance is called statistically significant.

A few more things… Double-blind: neither the subjects nor the person administering the treatment knew which treatment any subject had received Lack of realism is a major weakness of experiments. Is it possible to duplicate the conditions that we want?