Consumer Behavior: Buying, Having, Being
13th EditionMichael R Solomon
449 solutions
HDEV5
6th EditionSpencer A. Rathus
380 solutions
Myers' Psychology for AP
2nd EditionDavid G Myers
900 solutions
Myers' Psychology for the AP Course
3rd EditionC. Nathan DeWall, David G Myers
955 solutions
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EXPERIMENTAL DESIGN IL SINGLE-FACTOR DESIGNS
Terms in this set (27)
four varieties of single-factor designs
- independent groups
- matched groups
- nonequivalent groups
- repeated measures
Single Factor-
Two Level
Independent groups designs
Between-subjects, single factor designs
Independent groups designs
- Manipulated independent variable
- Random assignment to create equivalent groups
Research Example 11
-IV à manipulated type of note-taking
■Laptop note-taking
■Handwritten note-taking
-DV à performance on memory test
-Other concepts: conceptual replication, what's next thinking, and ecological validity
One Factor(IV) with 2 levels (T-test)
Single-Factor—Two Levels
Matched Groups Designs
Between-subjects, single factor designs (continued)
Matched Groups Designs
- Manipulated independent variable
- Matching to produce equivalent groups
Research Example 12
-IV à type of social skills training
■Direct teaching
■Play activities
-Matching variable à Autism Quotient
-DV à Social Interaction
Observation Code
-Other concepts: operational definitions, double-blind procedure, inter-rater reliability
One factor, 2 levels (t-test)
Single-Factor—Two Levels
nonequivalent groups/ Post Facto Designs
Between-subjects, single factor designs (continued)
Ex Post Facto Designs
- Subject variable as an independent variable
- Deliberate attempts to select participants to reduce
nonequivalence
Research Example 13
-IV à whether or not traumatic brain injury (TBI) had occurred
■Experimental group à had experienced TBI
■Control group à no TBI
-DV à ability to detect insincerity others
-Other concepts: matching, external validity addressed
1 factor, 2 levels (t-test)
Single-Factor—Two Levels
Within Subjects Design/ Repeated Measures
Within-subjects, single
factor designs
Also called repeated measures designs
- Famous historical example à Stroop (Box 7.1)Used reverse counterbalancing
- Manipulated independent variable
- All Ss participate in all levels of the independent variable
Research Example 14
-IV à whether or not you share your experience with another person
■Shared
■Unshared
-DV à ratings of liking and of flavorfulness of chocolate
-Other concepts: confederate, cover story, what's next thinking
One Factor,
2 levels
t-test
Single-Factor—More Than Two Levels
Between-subjects, multilevel designs: Bransford and Johnson's (1972) 'laundry study'
-One IV, three levels, independent groups
■No context (no topic presented)
■Context before (topic presented before reading paragraph)
■Context after (topic presented afterreading paragraph)
-DV à recall of paragraph's ideas
Single-Factor—More Than Two Levels
Multilevel independent groups design
Multilevel independent groups design
Research Example 15
-IV à number of people with children
■Alone
■Bystander (with 2 other children who could help)
■Bystander-Unavailable (with 2 other children who could not help)
-DV à whether or not child (participant) helped teacher
-Other concepts: operational definitions, confederates, inter-rater
reliability
one factor/IV, 3 levels
(ANOVA)
Single-Factor—More Than Two Levels
Within-subjects, multilevel designs
Within-subjects, multilevel designs (continued)
Research Example 13
-Multilevel repeated measures
-IV = listening experience
■Listening to Mozart
■Listening to a rainstorm
■Control - no listening
-DV = recall of digits
-Other concepts: counterbalancing via 3x3
Latin square, cover story
Describe two reasons for using more than two levels of an independent variable
Single-Factor—More Than Two Levels Between-subjects, multilevel designs
-Advantage #1 à ability to discover nonlinear effects
- Advantage #2 à ability to rule out alternative explanations
one factor, 3 levels (One Way ANOVA)
Describe the goals of the Ebbinghaus memory research, his methodology, and the results he obtained
...
Analyzing Data from Single-Factor Designs
-t test assumptions
-t test for independent samples
-t test for related samples
t-test assumptions
-Interval or ratio scale data
-Data normally distributed
(or close)
-Homogeneity of variance
t-test for independent samples
-Independent groups designs
-Nonequivalent groups designs
t test for related samples
- matched groups designs
- repeated measures designs
Analyzing single-factor, multilevel designs
- Multiple t-tests inappropriate
■Increases chances of Type I error (DO NOT DO)
-one-factor Analysis of Variance (ANOVA)
One Factor Analysis of Variance (ANOVA)
One-way ANOVA for independent groups
-Multilevel independent groups designs
-Multilevel ex post facto designs
One-way ANOVA for repeated measures
-Multilevel matched groups designs
-Multilevel repeated-measures
designs
Once overall significant effect found, then post hoc testing
-Comparing each level of IV against each other level
three special types of control groups
placebo, wait list, and yoked
Special-purpose control groups may be used to compare the effect of experimental treatments to no-treatment controls.
Placebo control groups
Placebo - inactive substance
- think they are being treated but they are not
Waiting list control groups
To insure equivalent groups in a study of program effectiveness
Research Example 17
■IV à exposure to subliminal tapes
-Experimental à weight loss tape
-Placebo control à dental pain tape (told was weight loss tape)
-Wait list control à no tape until wait was
over
■DV à weight loss (equal amount for all three groups)
■Other concepts: pilot study, Hawthorne effect, double-blind procedure
Yoked control groups
Each control group subject "yoked" to an experimental group subject
Research Example 18
-IV à treatment for stress
■Experimental à EMDR therapy
■Yoked control à same instructions without eye movements
■Each yoked participant matched with an
experimental participant in terms of session length
-DV à pretest-posttest changes in self-reported stress
-Other concepts: Example of failure to reject null hypothesis that nonetheless has some value
when to use an independent samples t-test
when the design is between subjects design
when to use a dependent samples t-test, when doing an inferential analysis of a single-factor, two-level design
A t-test for independent means test two distinct groups of participants, each group is tested once. -A test for dependent means tests one group of participants, and each participant is tested twice.
Understand why a one-way ANOVA, rather than multiple t-tests, is the appropriate analysis when examining data from single-factor, multilevel studies
more than 2 levels requires ANOVA not t-test
Understand why post hoc statistical analyses typically accompany 1-factor ANOVAs for single-factor, multilevel studies
Post Hoc are responsible for analyzing the data from more than 2 levels
In a scientific study, post hoc analysis consists of statistical analyses that were specified after the data were seen. This typically creates a multiple testing problem because each potential analysis is effectively a statistical test
t Test
-The most basic statistical test that measures group differences is the t test
-T test: analyzes significant differences between 2 group means
uEx: Do males and females have significantly different SAT scores?
One-way Analysis of Variance (ANOVA)
-ANOVA: test the significance of group differences between 2 or more means as it analyzes variation between
-We use ANOVAs when the IV is defined as having 2 or more categories and the DV is quantitative
-Ex: Do adolescents from low, middle, and high SES families have different scores have different scores on an AIDS knowledge test?
-ANOVA only determines the significance of group differences and does not identify which groups are significantly different, post hoc tests
are usually conducted in conjunction with ANOVA
Factorial ANOVA
an analysis of variance involving two or more independent variables or predictors.
-Extends ANOVA to research scenarios with 2 or more IVs that are categorical
-Ex: Do 3rd grade students have different math achievement scores based upon instructional treatment and gender?
-Post hoc tests are used to determine specific group differences
EXAM #1 Terms and Charts
133 terms
ale8828
PSYC 361 Week 5 EXAM #1
96 terms
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PSYC 361 Week 4 EXAM #1
111 terms
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PSYC 361 Week 3 EXAM #1
67 terms
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