Research Methods 4

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Cross-Sectional Designs:
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A research design in which investigators compare groups of subjects of differing age who are observed at a single point in time.
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experimental contamination:
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a situation that occurs when participants in one experimental condition are indirectly affected by the independent variable in another experimental condition because they interacted with participants in the other condition
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generational effects:
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when a particular generation has had certain experiences, their experiences make them politically extinct
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interrupted time series design with a reversal:
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a quasi-experimental design resembling the one-group pretest-posttest design but with a series of observations (measurements) before and after the treatment manipulation.
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interrupted time series design with multiple replications:
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a quasi-experimental design resembling the one-group pretest-posttest design but with a series of observations (measurements) before and after the treatment manipulation.
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local history effect:
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something else may happen to one group that does not happen to the other group (also called a selection-by-history interaction)
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longitudinal design:
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A research design in which investigators observe one group of subjects repeatedly over a period of time.
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nonequivalent control group design:
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used when equivalent one cannot be isolated
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nonequivalent groups posttest-only design:
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a between-subjects design with at least two groups of participants that uses a subject variable or that creates groups that are nonequivalent
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nonequivalent groups pretest-posttest design:
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a between-subjects design with at least two groups of participants that uses a subject variable or that creates groups that are nonequivalent
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one-group pretest-post test design:
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A quasi-experimental design in which the subjects in the experimental group are measure before and after the treatment is adminstered, but there is no control group
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pre-experimental design:
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When a single group is used in a research or two groups are not equivalent.
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quasi-experimental designs:
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Research method similar to an experimental design except that it makes use of naturally occurring groups rather than randomly assigning subjects to groups.
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quasi-independent variable:
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Variable selected (not manipulated) to create groups to compare (groups are selected)
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regression to the mean:
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The tendency for extreme scorers on one measurement to move (regress) closer to the mean on a later measurement causing a change that would normally not happen in the population.
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selection bias:
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Errors in the selection and placement of subjects into groups that results in differences between groups which could effect the results of an experiment.
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time series design:
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A research design where subjects are measured at specific times before and after the treatment has been administered in order to determine the long term effects of the treatment
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natural settings:
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involves the observation of ongoing behavior as it occurs naturally with no intrusion or intervention by the researcher
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contrived settings:
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involves the observation of behavior in settings that are arranged specifically for observing and recording behavior
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reactance:
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subjects know they are being observed
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How to minimize reactance?
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Researchers may conceal the fact that they are observing and recording behavior. (disguised observation)
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structured observations:
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the right choice: check lists, categories of behavior, ratings, time measurements (latency, duration)
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3 ways to record behavioral observations:
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1. Does it occur in natural or contrived setting? 2. Will participant know they are being observed? 3. How will participant’s behavior be recorded?
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experience sampling:
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measures the frequency of mental experiences; thought, mood, mind
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unstructured observations:
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a) Field notes: a running record, a continuous record (more-like anthropology) b) Narrative: Not quantified; how to turn into #s?
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probability sample:
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a sample in which every element in the population has a known statistical likelihood of being selected
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sampling error:
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Random error due to the chance that a sample may not accurately reflect the characteristics of the population.
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What factors influence the size of sampling error?
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1. # of groups (difference among means) 2. lack of experimental control 3. Intraparticipant variance 4. Unsystematic, uncontrolled, unidentified
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drawbacks of phone surveying?
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not deep, trusting self-reports
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stratified sampling:
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-Involves dividing the population into distinct sub groups (layers) and selecting a separate from each layer in the same proportion that they occur in the target population
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What is the problem of non-response?
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non-completion decreases representativeness; participants must also complete survey once selected.
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external validity:
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The extent to which the results of a study can be generalized to other populations or settings than the sample that was studied.
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Type of sampling most used in psychological research?
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1. non-probability 2. non-random sampling 3. convenience sampling
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Convenience samples of college students?
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1. Choosing random participants readily available 2. Student’s differ from average person 3. Large sample size
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Validity?
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Test is supposed to measures what it was intended to, if it does not then the test is not meaningful or valid. Strict procedures, ensuring patient effort, performance & equipment accuracy & calibration
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Types of response format on surveys?
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face to face, web, phone, mail
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social desirability:
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responding in ways you believe the experimenter will approve of
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case studies:
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Intensive investigation of a single or a few individuals. This is generally a non-experimental method. Ex post facto: after the fact or maybe during the fact.
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4 uses of case studies:
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1. Source of ideas for further research 2. Describe rare phenomena 3. Test theories
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Why are people reluctant to trust case studies?
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retrospective, ex post facto, possible experimenter bias, demand characteristics, observer bias
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Quasis differ from real experiments if one or both of the following occur:
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•The subjects are not randomly assigned to conditions •Usually the experimenter does not control the IV
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When/Why use a quasi?
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to study real world situations where experimentation is not possible and for program evaluation.
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Threats to internal validity:
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history, maturation, pretesting effects, statistical regression, DV changes, groups are unequal, differential attrition and history.
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Why doesn’t author like pretest-post test design?
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It has a bad, poor, low, internal validity design.
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longitudinal:
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follow a group for a long period of time, tracking changes; often used in developmental research
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cross sectional:
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compare age-effects, compare groups of different ages at the time the study is conducted.
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cohort effects:
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Cohort effect enables us to understand older adults from different cultures and different geographical areas
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Time series:
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make a series of measurements of the DV; often uses records or statistics that are otherwise being collected
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program evaluation:
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evaluate effectiveness of a program
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Why use quasi for program evaluation?
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To study real world situations where experimentation is not possible
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Donald Campbell’s contributions?
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popularized quasi-designs; social & educational programs; internal & external validity
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Criteria of cause-and-effect?
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1. The presumed causal variable preceded the effect in time. 2. The Cause and Effect co-vary. 3. All other alt. explanations of results are eliminated through randomization or experimental control.
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patched-up designs:
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rather than adhering blindly to 1 particular design, helps provide meaningful data.
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what does patch-up refer to?
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refers to increasing confidence in quasi-experimental results
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experiments:
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active manipulation of the independent variable
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non-experimental methods:
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no control over subject assignment; usually not of IV
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4 non-experimental methods:
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1. quasi 2. surveys 3. behavioral observations 4. case studies
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quasi experiments
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\”as-if\” experiments; sort of experiments
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Quasi experiments in some ways look like experiments _________
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because they are experimental and have a control conditiong
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A good quasi design uses both a _______:
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pretest and control group
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Bad quasi-experimental design factors:
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poorly designed, poor control, low validity
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Selection Threat
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groups may differ in important ways before the study even starts
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Maturation Threat
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short or long term changes in participant’s may change their behaviors (boredom, physical development)
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Attrition
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people may drop out of the study; those who do may differ from those who remain
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History Threat
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some minor or major event may occur during a study that changes the participants’ behaviors

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