RD Topic 6.pdf

EDWARDS—RESEARCH METHODS LECTURE NOTES PAGE 42 Topic #6 QUASI–EXPERIMENTAL DESIGNS Central issue is, of course, one of research validity Q–designs are research procedures in which...

EDWARDS—RESEARCH METHODS LECTURE NOTES PAGE 42 Topic #6 QUASI–EXPERIMENTAL DESIGNS Central issue is, of course, one of research validity Q–designs are research procedures in which participants must be and are selected for different conditions from pre–existing groups (e.g., you cannot randomly assign people to be male or female; Atlanta office or Philadelphia office; manager or nonmanager; low or high SES). They are studies in which levels of the IV are selected from pre–existing values and not created through manipulation by the researcher. In true experimental designs, participants are randomly assigned to experimental and control groups; whereas with Q–experimental designs, they are NOT!! A Q–experiment DOES NOT permit the researcher to control the assignment of participants to conditions or groups. RANDOM ASSIGNMENT TO GROUPS IS THE BASIC DIFFERENCE BETWEEN TRUE AND Q–EXPERIMENTAL DESIGNS. Q–designs are characterized by lower levels of control over the WHO, WHAT, WHEN, WHERE and HOW of the study. Although the presence of uncontrolled or confounded variables reduces the internal validity of Q–experiments, they do not necessarily render them invalid. Basically, the likelihood that confounding variables are responsible for the study outcome must be evaluated. Types Of Q–Experimental Designs 1. Nonequivalent Control Group Designs—research designs having both experimental and control groups but the participants are NOT randomly assigned to these groups this is the most typical type of Q–design problems with this type of design have to do with how to compare the results between groups when they are not equivalent to begin with. EDWARDS—RESEARCH METHODS LECTURE NOTES PAGE 43 EXAMPLE—EFFECT OF WORK SCHEDULES ON PRODUCTIVITY ALLOCATION PRETEST TREATMENT POSTTEST TO GROUPS GROUP I ANY YES YES YES NONRANDOM GROUP II METHOD YES NO YES Q–designs that employ nonequivalent control groups with pre– and posttest may or may not be interpretable. Interpretability depends on whether the pattern of results obtained can be accounted for by possible differences between the groups or by something else in the study. Examples of nonequivalent control group designs A. Delayed Control Group Designs—nonequivalent control group design in which the testing of one group is deferred. i.e., the two groups are tested sequentially with an appreciable time interval between the two EDWARDS—RESEARCH METHODS LECTURE NOTES PAGE 44 B. Mixed Factorial Designs—have one between–subjects variable and one within–subjects variable (e.g., study of trait [between] and state regulatory focus [within] and impact on job performance). State Regulatory Focus Prevention Promotion S1 S1 Prevention S2 S2.... Trait S20 S20 Regulatory Focus S1 S1 S2 S2 Promotion.... S20 S20 2. Designs Without Control Groups A. Interrupted Time–Series Designs—this design allows the same group to be compared over time by considering the trend of the data before and after the treatment. EDWARDS—RESEARCH METHODS LECTURE NOTES PAGE 45 A variation of interrupted time–series design, which is really NOT a design without control groups, is the Multiple Time–Series Designs. This is a time–series design in which a control and experimental group are included to rule out HISTORY as a rival hypothesis (e.g., compare drunk driving accidents in Michigan to Wisconsin before and after Michigan raised the drinking age from 18 to 21; Wisconsin is the control group because they retained the 18-year-old limit during the months of the study). B. Repeated Treatment Designs—this research design allows the same group to be compared by measuring subjects' responses before and after repeated treatments. QUESTIONS Can we make causal inferences based on Q–designs? How strong will these inferences be?