Exam 1 Review Flashcards
Where neither the subjects or the investigators are aware of the identity of the treatment groups until after the data are collected.
Double blinding
Where the person collecting the data knows whether the subject is in the control group or the experimental group but the subjects do not.
Single blinding
Allows researchers to assess whether there is an interaction between the treatment and the pretest.
Solomon’s four-group design
Each participant is exposed to all of the treatments administered in an experiment, according to a randomly selected sequence, and the effects of these treatments are compared within each individual.
- Each participant as his or her own control as a basis for evaluating different treatment effects.
- The same participants will perform differently under one tx condition as compared to another; thus, the influence of the independent variable on a dependent variable can be determined.
Repeated-measures design
Has only one group of subjects. Subjects receive all levels of the independent variable at different times.
- The researcher controls for subject characteristics.
Within-subjects design
- Participants are randomly assigned to one of two or more conditions.
- Assumes that all groups are equal, expect that that received the experimental treatment.
Between-subjects design
The average effect of an independent variable across levels of the dependent variable.
Main effect
The joint effect of two independent variables - how the two treatments combine or interact to influence certain outcomes.
Interaction effect
Combines within-subjects and between-subjects designs and are used to investigate the effects of treatment for which carryover effects would be a problem while repeatedly sampling behavior across time or trials.
Mixed model design
Employ more than 1 I.V.
Have one-way, two-way, and three-way types of these designs, each indicating the number of variables involved in the design.
Can be used to examine both different treatment effects resulting from alternative independent variables and these treatment effects resulting from alternative independent variables and these treatment effects at different levelsof the same independent variables.
Factorial design
Each subject has an equal chance of being assigned to any experimental group. In clinical SLP research, using small sample sizes, randomized sampling is not ideal.
Random assignment
A group of individuals drawn by a procedure in which all of the individuals have an “equal and independent” chance of being selected.
Simple random sampling
Easier than simple random sampling. Use if the sample is very large.
Systematic random sampling
A sample selected so that certain subgroups in the population are adequately represented in the sample.
Stratified random sampling
A multistage sampling procedure in which smaller samples are selected from larger units or clusters. Often used to assure balanced, geograrphical representation of a population.
Cluster sampling
