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Basic Considerations in Experimental Design

Basic Considerations in Experimental Design. Chapters 6 and 7. Step 1. Step 2. Step 3. Step 4. Participant Selection. Participant Assignment. Design and Consistency Of Treatment. Interpretation of Hypothesis. Control Potential Confounds. 1. Null hypothesis, E = C.

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Basic Considerations in Experimental Design

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  1. Basic Considerations in Experimental Design Chapters 6 and 7

  2. Step 1 Step 2 Step 3 Step 4 Participant Selection Participant Assignment Design and Consistency Of Treatment Interpretation of Hypothesis Control Potential Confounds 1. Null hypothesis, E = C Experimental Group T M Compare 2. Confound hypothesis, E ≠ C Population Participants Control Group M 3. Research hypothesis, E ≠ C Choose participants for experiment Assign participants to groups Perform Experiment Balance scientific and practical considerations Can we assume E = C? Is E treated differently From C only in terms of Independent variable? Does E differ from C Statistically, and why?

  3. Selecting Participants • Scientific Considerations • How participants are sampled from the population affects external validity • Population • Group of people to which you want your results to apply • External Validity • the extent to which the results of a study can be applied to a larger group or to other circumstances • A wide variety of sampling techniques is available • Two Main types of sampling • Probability • predetermined chance of any individual in the population being selected for the study • Nonprobability • Typically nonrandom sampling

  4. Probability Sampling Simple random sampling Systematic sampling Stratified random sampling Cluster sampling Multistage sampling Nonprobability Sampling Convenience sampling Quota sampling Snowball sampling Sampling Techniques • Probability sampling techniques typically result in greater external validity.

  5. Controlling Potential Confounds • Goal of experiment is to “rule out” alternate explanations of what affected dependent variable • Confounds are threats to internal validity • Internal validity • Is there another factor (other than the independent variable) that could explain the results of the experiment? • Can be controlled through • appropriately assigning participants to experimental conditions (individual differences) • appropriate experimental design (e.g., control group) • Consistency in delivering experimental treatment

  6. Assigning Participants to Groups • Random assignment helps control the potential effects of all individual differences • Random assignment increases the likelihood that all individual differences will be equally distributed across experimental groups. • The effects are NOT eliminated • Each group EQUALLY affected by them • Random assignment allows us to rule out individual differences as potential “cause” of dependent variable

  7. Internal Validity • Confounds Controlled by Experimental Design • History • Maturation • Testing • Instrumentation • Statistical Regression • Selection • Mortality • Selection-Maturation • Confounds NOT controlled by Experimental Design • Diffusion of Treatment • Compensatory Equalization • Compensatory Rivalry

  8. Disadvantages Controls none of the threats to internal or external validity Basically worthless Advantages Can potentially provide information for speculation about training effectiveness Preexperimental Designs Post with no Control Group Training Posttest

  9. Cannot rule out any threats to internal or external validity Except possibly mortality Advantages Can determine if change occurred May be able to understand mortality Preexperimental Designs Pre – Post with no Control Group Pretest Training Posttest

  10. Experimental Designs Posttest-Only Control Group Design Experimental Training Posttest Random Assignment Group Differences Control Posttest

  11. Experimental Designs Pre – Post with Control Group Pretest Experimental Training Posttest Group Differences Group Differences Pretest Control Posttest

  12. Experimental Designs Solomon Four Group Design Group 1 Pretest Training Posttest Group 2 Pretest No Training Posttest Group 3 Training Posttest Group 4 Posttest No Training

  13. Criteria for True Experiments • Participants must be randomly assigned • Must be at least 2 levels of independent variable • Must control for major threats to internal validity • Compares two alternative theoretical positions • e.g., Platt and strong inference • Not all scientists agree this criteria is necessary for a true experiment

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