© 2001 dr. laura snodgrass, ph.d.1 conducting experiments choosing methods sampling and sample size...

© 2001 Dr. Laura Snodgrass, Ph.D. 1

Conducting Experiments

• Choosing methods

• Sampling and sample size

• Independent variables

• Dependent variables

• Controls

• Debugging


Choosing Methods

• Laboratory experiments can be artificial– too much control

• Field experiment– more natural setting– lose some control

• Ethical and practical concerns

• Participant variables– quasi-experimental designs


Choosing

• Description and prediction can be done without casual concerns

• Human complexity– number of interacting causal variables

• Neglect of individual differences– averaged across groups

• Social responsibility– objectivity– values– Gergen’s paradigm II


Sampling

• Generalization requires adequate sampling

• Populations– you define population “of interest”

• Why sample– cost-benefit analysis - law of diminishing returns– destruction of items tested– infinite populations– may increase accuracy


Participant Sampling

• Psychology as the study of white rats and college sophomores

• Generalization from– different species– different groups

• students have different pressures and performance anxiety

• volunteers differ from non-volunteers


Sampling Techniques

• Systematic random sampling

• Stratified random sampling

• Cluster sampling

• Haphazard or convenience sampling

• Quota sampling


Other Types of Samples

• Experimenters as samples– gender, age, ethnicity, behavior, dress

• Stimulus sampling– representative of pop of stimuli– random or controlled

• Condition sampling

• Response sampling– number of dependent measures– number of trials


Sample Size

• Tradition– look in journals

• Expected variability in results– consistency within and between participants

• Planned statistical analysis– parametric versus nonparametric– significance level– size of difference between means expected– do a power analysis


Independent Variables

• Setting the stage– informed consent– brief explanation of what is expected

• Types of manipulations– straightforward– staged

• to create a psychological state• to simulate a real world situation• use confederates



• Strength of manipulation - choosing levels– number of levels– range– how close together are the levels

• Combining variables– incomplete or unbalanced designs (leaving out some cells)

• redundant or illogical• data from literature• too many cells to fill



• Confounding– environmental confounds

• the “Hawthorne Effect”– participant confounds

• equality of groups

• Cost of manipulation


Dependent Measures

• Types of measures– self-report

• rating scales– behavioral

• reaction time• error rate

– physiological• GSR, heart rate


Dependent measures

• Sensitivity– ceiling effect - too easy– floor effect - too hard– no effect

• Multiple Measures– e.g. time perception

• Ethics of measures (e.g. privacy)

• Cost


Other Controls

• Participant Effects– loss of subjects– volunteers– social desirability– demand characteristics

• deception• filler items• placebo groups


Controls

• Experimenter effects– experimenter bias or expectancy effects

• subtle coaching• recording errors• teacher expectancy

• Solutions– training– run conditions simultaneously– single-blind– double-blind


Debugging

• Research proposals– getting feedback from others

• Pilot studies

• Manipulations checks– especially in pilot study– can explain non-significant results


Data Defects

• Missing data– some statistics allow for missing daat– can replace with averaging techniques– SPSS have several missing data options

• Extreme score or outliers– techniques for discarding– replace with averaging

• Appropriate Statistics!!!!!!!!!!!!!!!!!

© 2001 dr. laura snodgrass, ph.d.1 conducting experiments choosing methods sampling and sample size...

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