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Research methods, design, analysis 12th ed. Chapter 6,10.
Terms in this set (78)
correctness, truthfulness of inferences made from a research study
Four major types of Validity
1. Statistical conclusion validity (SCV)
2. Construct validity (CV)
3. Internal validity (IntV)
4. External validity (EV)
Statistical construct validity
Validity of the inference made about whether the IV + DV=co-vary.
Validity of the inference about the higher order constructs from the operations used to represent them.
Validity of the inference that the IV's + Dv's are causally related.
Validity of the inference about whether the causal relationship holds over people, settings, treatment variables, measurement variables, and time.
Observed relationship is probably not due to chance.
Participant reactivity to the experimental situation
Research participants' motives and tendencies that affect their perceptions of situation and their responses to the DV.
Any of the cues available in an experiment such as instructions, rumors, or setting characteristics that influence responses of participants
List some threats to Construct validity
1. inadequate explanation of construct:
2. Construct confounding:
3. Mono-operation bias
4. Mono- method bias
5. Treatment-sensitive factorial structure
Inadequate explanation of construct
Construct is not adequately explained and analyzed, can lead to a set of inadequate representations of construct
operations used in a study represent more than 1 construct
a study uses only one method (eg. physiological recording) to operationalize a construct, Method used might influence results
a study uses only one operationalization of a construct. Typically results in and under representation of the construct +lowers construct validity
Treatment -sensitive factorial structure
instrumentation change that occurs because of the experimental treatment.
Participants' motivation to respond in such a way as to present themselves in the most positive manner
Actions and characteristics of researchers that influence the responses of participants
Baising experimenter effects attributable to the researchers' expectations about the outcome of the experiment
Biasing experimenter effects attributable to the physical and psychological characteristics of the researcher
correctness of inferences made by researchers about cause and effect
Occurs when an extraneous variable co-occurs with the IV and affects the DV
Confounding extraneous variable
An extraneous variable that co-occurs with the IV and affects the DV
The influence of an extraneous variable is same on all of the independent variable groups
Equating the groups
Using control strategies to make the influence of extraneous variables constant across the independent variable groups so that only the systematic difference between the groups is due to the influence of the independent variable
Any event that can produce the outcome, other than the treatment condition, that occurs during study before posttest measurement
Groups in a multi-group design experience different history events that result in differences on the DV
Any physical or mental change that occurs with the passage of time and affects DV scores
Changes from pretest to posttest in the assessment or measurement of the DV
Changes in a person's score on the 2nd administration of a test resulting from having previously taken the test
Effects that appear to be due to the treatment but are due to regression to the mean
Regression toward the mean
Synonym for regression artifacts
Loss of participants because they don't show up or they drop out of a research study
In a multi-group design, groups become different on an extraneous variable because of the differences in the loss of participants across the group
Production of non-equivalent groups because a different selection procedure operates across the groups
Additive and interactive effects
Differences between groups is produced because of the combined effect of two or more threats to internal validity
Groups are exposed to the same history event, but react differently because they were not equated
Groups undergo different rates of maturation because they were not equated
Groups react to changes in instrumentation differently because the were not equated
Groups react differently because they were not equated
groups show different amounts of regression to the mean, because they were not equated.
List the extraneous variables that are threats to internal validity?
5. regression artifacts
8. Additive and Interactive effects
Degree to which the study results can be generalized to and across other people, settings, treatments, outcomes, and times
Degree to which the study results can be generalized to and across the people in the target population
The large population to which the researcher would like to generalize the study results
The population of research participants that is practically available to the investigator
degree to which the results of a study can be generalized across settings and environmental conditions
degree to which the results can be generalized across time
Values on the DV vary by season
Any type of systematic up-and-down movement on the DV over time
Treatment variation validity
degree to which the results of a study can be generalized across variations in treatment
degree to which the results of a study can be generalized across different but related DV's
Types of external validity's 5 broad categories?
1. population validity
2. ecological validity
3. treatment variation validity
4. outcome validity
5. time validity
A research design in which an experimental procedure is applied but all extraneous variables are not controlled
Structures and procedures used in constructing research designs
Continuum of experimental research designs?
1. weak experimental designs
2. Quasi-experimental designs
3. Strong experimental designs
Non-equivalent comparison group design
quasi-experimental design in which the results obtained from nonequivalent experimental and control groups are compared
Principles used to rival explanations in quasi-experiments?
1. identification and study of plausible threats to internal validity
2. Control by design
3. Coherent pattern matching
Explain 'identification and study of plausible threats to internal validity'
Principle involves identifying plausible rival explanations + probing and investigating them to determine how likely it is that they can explain the co-variation between the treatment and the outcome
Explain 'control by design'
Principle involves adding design elements such as additional pretest time points or additional control groups, to either eliminate a rival explanation or obtain evidence about the plausibility of the rival explanation
Explain 'coherent pattern matching'
Principle can be used when a complex prediction can be made about a causal hypothesis, if there are few, if any rival explanations that would make the same prediction.
Major design components that are usually available to a researcher?
1. control or comparison groups (0/1/<1)
2. pretest (0/1/<1)
3. posttest (1/<1)
4. within-participants and/or between-participants' IV's
5. inclusion of one ore more theoretically interesting IV's
6. measurement of one or more theoretically interesting variables
Can view the quasi-experimental designs presented as?
design improvements upon weak designs
Types of Quasi-experimental designs?
1. nonequivalent comparison group design
2. Interrupted time series design
3. Regression discontinuity design
non-equivalent comparison group design
A quasi-experimental design in which the results obtained from non-equivalent experimental and control groups are compared
Selection and additive/interaction threats to internal validity of the non-comparison group design?
1. Selection bias: Because groups are nonequivalent=always be a potential for selection bias;
2. Selection-attrition bias: pretest allows examination of nature of attrition to see if there is a difference between those that drop-out or do not complete experiment and those that do;
3. Selection-maturation bias: might exist if one of the group participants becomes more experienced, tired, bored than others in the group.
4. Selection-instrumentation bias: might exist if nonequivalent groups of participants start at different points on pretest, particularly if the measuring instrument doesn't have equal intervals.
Increasing control and experimental group effects
An outcome in which the experimental and the control groups differ at pretesting, and both increase from pretesting to posttesting, but experimental group increases at a faster rate.
Selection maturation effect
Participants in one group experience a different rate of maturation than participants in another group
Selection history effect
Extraneous event occurring between pretest and posttest, influences participants in one group differently than participants in another group.
Selection instrumentation effect
Participants' scores in one group are affected by the process of measurement differently than participants in another group.
Participants that drop out of one group are dissimilar to those in another group
Participants in one group display a different rate of regression to the mean than participants in another group
An outcome in which the experimental performs better than the control group at pretesting, and only the experimental group's scores change from pretesting to posttesting
An outcome in which the control group performs better than the experimental group at pretesting, but only the experimental group improves from pre- to posttesting
An outcome in which the control group performs better at pretesting but the experimental group performs better at posttesting
Interrupted time-series design
A quasi-experimental design in which a treatment effect is assessed by comparing the pattern of pre- and posttest scores for a single group of research participants
Regression discontinuity design
A design that assigns participants to groups based on their scores on an assignment variable and assesses the effect of a treatment by looking for a discontinuity in the groups regression lines.
Measure used to assign participants to experimental and control groups. Those with scores below cut-off score are assigned to one group, those with scores above the cutoff are also assigned to the other group.
Requirements of the regression discontinuity design
1. Assignment to comparison groups must be based only on cut-off score
2. Cutoff score should ideally be located at the mean of the distribution of scores. Cutoff=to the extremes, lower the statistical power of design
3. The assignment variable must at least be an ordinal variable, best if it is a continuous variable
4. Assignment to comparison groups must be under the control of the experimenter to avoid a selection bias
Recommended textbook explanations
Myers' Psychology for AP
David G Myers
A Concise Introduction To Logic (Mindtap Course List)
Lori Watson, Patrick J. Hurley
Psychology: Principles in Practice
Spencer A. Rathus
Arlene Lacombe, Kathryn Dumper, Rose Spielman, William Jenkins
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