PSY 718 Test 2 Vocab
CHAPTER 9
Analysis of covariance: A statistical procedure in which group means are compared after adjusting for pretest differences
Factorial design: Two or more independent variables are studied to determine
their separate and joint effects on the dependent variable
Between-subjects independent variable: Type of independent variable where different participants receive different levels of the independent variable
Cell: Combination of levels of two or more independent variables
Cell mean: The average score of the participants in a single cell
Marginal mean: The average score of all participants receiving one level of an independent variable
Main effect: The influence of one independent variable on the dependent variable
Interaction effect: When the effect of two or more IVs on the DV is more complex than indicated by the main effects
Two-way interaction: The effect of one independent variable on the dependent variable varies with the different levels of the other independent variable
Within-subjects independent variable: Type of independent variable where all participants receive all levels of the independent variable
Factorial design based on a mixed model: A factorial design that uses a combination of Within-participants and between-participants independent variables
Three-way interaction: A two-way interaction that changes at the different levels of the
third independent variable
CHAPTER 11
Single-case research designs: Research design in which a single participant or a single group of individuals is used to investigate the influence of a treatment condition
ABA design: A single-case design in which the response to the treatment condition is compared to baseline responses recorded before and after treatment
Baseline: The target behavior of the participant in its naturally occurring state or prior to presentation of the treatment condition
Reversal: Change of behavior back to baseline level after withdrawal of treatment
ABAB design: Extension to ABA design to include reintroduction of the treatment condition
Withdrawal: Removal of the treatment condition
Reversal design: A design in which the treatment condition is applied to an alternative but incompatible behavior so that a reversal in behavior is produced
Interaction design: Single-case design used to identify interaction effects
Interaction effect in single-case research: The combined influence of two or more independent variables
Interaction design: Single-case design used to identify interaction effects
Interaction effect in single-case research: The combined influence of two or more independent variables
Multiple-baseline design: A single-case design in which the treatment condition is successively administered to several target participants, target outcomes, or target settings
Interdependence: Violation of design assumption in which changing one target (participant, outcome, or setting) produces changes in the remaining targets
Changing-criterion design: A single-case design in which a participant’s behavior is gradually shaped by changing the criterion for success during successive treatment periods
Stable baseline: A set of responses characterized by the absence of trend and little variability
Experimental criterion: In single-case research, repeated demonstration that a behavioral change occurs when the treatment is introduced
Therapeutic criterion: Demonstration that the treatment condition has eliminated a disorder or has improved everyday functioning
Social validation: Determination by others that the treatment condition has significantly changed the participant’s functioning
Social comparison method: A social validation method in which the participant is compared with nondeviant peers
Subjective evaluation method: Social validation method where others’ are asked if they perceive a change in the participant’s behavior
CHAPTER 10
Quasi-experimental design: A research design in which an experimental procedure is applied but all extraneous variables are not controlled
Design components: Structures and procedures used in constructing research designs
Nonequivalent comparison group design: A quasi-experimental design in which the
results obtained from nonequivalent experimental and control groups are compared
Increasing control and experimental groups effect: An outcome in which the experimental and the control groups differ at pretesting and both increase from pre- to posttesting, but the 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: An 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
Selection-attrition effect: Participants that drop out of one group are dissimilar to those in another group
Selection-regression effect:Participants in one group display a different rate of regression to the mean than participants in another group
Experimental-Group-Higher-than-Control-Group-at-Pretest Effect: An outcome in which the experimental performs better than the control group at pretesting, and only the experimental group’s scores change from pre- to posttesting
Experimental-Group-Lower-than-Control-Group-at-Pretest Effect: 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
Crossover effect: 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
Assignment measure: Measure used to assign participants to experimental and control groups. Those with scores below the cutoff score are assigned to one group, and those with scores above the cutoff are assigned to the other group
Chapter 6
Threats to internal validity and external validity
Research validity: Truthfulness of inferences made from a research study
Statistical conclusion validity: Validity of the inference made about whether the independent and dependent variables covary.
Construct validity: Validity of the inference about the higher-order constructs from the operations used to represent them.
Internal validity: Validity of the inference that the independent and dependent variables are causally related.
External validity: Validity of the inference about whether the causal relationship holds over people, settings, treatment variables, measurement variables, and time.
Participant reactivity to the experimental situation: Research participants’ motives and tendencies that affect their perceptions of the situation and their responses on the dependent variable
Demand Characteristics: Any of the cues available in an experiment, such as instructions, rumors, or setting characteristics, that influence the responses of participants
Experimenter effects: Actions and characteristics of researchers that influence the responses of participants
Experimenter expectancies: Biasing experimenter effects attributable to the researcher’s expectations about the outcome of the experiment
Experimenter attributes: Biasing experimenter effects attributable to the physical and psychological characteristics of the researcher
Confounding: Occurs when an extraneous variable co-occurs with the independent variable and affects the dependent variable
Confounding extraneous variable: An extraneous variable that co-occurs with the independent variable and affects the dependent variable
Constancy: 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 the only systematic difference between the groups is due to the influence of the independent variable
History: Any event that can produce the outcome, other than the treatment condition, that occurs during the study before posttest measurement
Differential history: The groups in a multigroup design experience different history events that result in differences on the dependent variable
Maturation: Any physical or mental change that occurs with the passage of time and affects dependent variable scores
Instrumentation: Changes from pretest to posttest in the assessment or measurement of the dependent variable
Testing effect: Changes in a person’s score on the second administration of a test resulting from having previously taken the test
Regression artifacts: Effects that appear to be due to the treatment but are due to regression to the mean
Regression toward the mean: A synonym for regression artifacts
Attrition: Loss of participants because they don’t show up or they drop out of the research study
Differential attrition: In a multigroup design, groups become different on an extraneous variable because of differences in the loss of participants across the groups
Selection: Production of nonequivalent 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
Selection-history: The groups are exposed to the same history event, but they react differently because they were not equated
Selection-maturation: The groups undergo different rates of maturation because they were not equated
Selection-instrumentation: The groups react to changes in instrumentation differently because they were not equated
Selection-testing: The groups react to the pretest differently, because they were not equated
Selection-regression Artifact: The groups show different amounts of regression to the mean, because they were not equated
Population validity: Degree to which the study results can be generalized to and across the people in the target population
Target population: The large population to which the researcher would like to generalize the study results
Accessible population: The population of research participants that is practically available to the investigator
Ecological validity: The degree to which the results of a study can be generalized across settings or environmental conditions
Temporal validity: The degree to which the results can be generalized across time
Seasonal variation: Values on the dependent variable vary by season
Cyclical variation: Any type of systematic up-and-down movement on the dependent variable over time
Treatment variation Validity: The degree to which the results of a study can be generalized across variations in the treatment
Outcome validity: The degree to which the results of a study can be generalized across different but related dependent variables
Weak experimental designs
Weak experimental designs: Designs that do not control for many extraneous variables and provide weak evidence of cause and effect
One-group pretest–posttest design: Design in which a treatment condition is interjected between a pretest and posttest of the dependent variable
Posttest-only design with nonequivalent groups: Design in which the performance of an experimental group is compared with that of a nonequivalent control group at the
Posttest
Posttest-only control-group design: Administration of a posttest to two or more randomly assigned groups of participants that receive the different levels of the independent variable