In what type of ANOVA is there one factor on which participants are tested more than once quizlet?

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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

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How many times are participants tested in the factorial ANOVA?

Why is the F test always nondirectional?

What is a simple analysis of variance also called?

When computing the degrees of freedom for ANOVA How is the within group estimate calculated?