Between- Subjects Design
-
Upload
iliana-house -
Category
Documents
-
view
33 -
download
0
description
Transcript of Between- Subjects Design
![Page 1: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/1.jpg)
Between- Subjects Design
Chapter 8
![Page 2: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/2.jpg)
Review
![Page 3: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/3.jpg)
Two types of Ex research
• Two basic research designs are used to obtain the groups of scores that are compared in an experiment:
• within-subjects design• between-subjects design.
![Page 4: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/4.jpg)
Within & Between designs
Within SubjectsStudents Silence Music
A 12 15B 13 14C 15 14D 14 15E 15 14
Between SubjectsStudents Silence Music
A 12 B 13 C 15 D 14 E 15 F 15G 14H 14I 15J 14
![Page 5: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/5.jpg)
Between subjects limitations
![Page 6: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/6.jpg)
1- More subjects required
To compare three different treatment conditions with 30 scores in each treatment, the between- subjects design requires 90 participants.
![Page 7: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/7.jpg)
2-Group Difference
Individual differences, may lead to group differences or assignment bias.
![Page 8: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/8.jpg)
Example
• If the participants in one group are generally older ( or smarter, or taller, or faster, etc.) than the participants in the other group, then the experiment has a confounding variable.
![Page 9: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/9.jpg)
3- Larger variance
Increases variance which makes it hard to find significant differences (explained later)
![Page 10: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/10.jpg)
Two types of confounding variables
• Confounding from individual differences, which is called assignment bias.
• Confounding from environmental variables.one group may be tested in a large room and
another group in a smaller room.
![Page 11: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/11.jpg)
Making equivalent groups
• Random Assignment ( Randomization)• Matching Groups ( Matched Assignment)• Holding Variables Constant or Restricting
Range of Variability
![Page 12: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/12.jpg)
1-Random Assignment
• It is relatively easy, and does not require any measurement or direct control of extraneous variables.
• However, random assignment is not perfect and cannot guarantee equivalent groups, especially when a small sample is used. Pure chance is not a dependable process for obtaining balanced equivalent groups.
![Page 13: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/13.jpg)
2-Matching Groups
• School records are used to determine the IQs of the participants, and each student is classified as high IQ, medium IQ, or low IQ. The high- IQ participants are distributed equally between the two groups; half is assigned to one group and the other half is assigned to the second group using restricted random assignment.
• However, matching requires pre-testing to measure the variable( s) being controlled,
• It can become difficult to match several variables simultaneously.
![Page 14: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/14.jpg)
3-Holding a variable constant
• For example, a researcher concerned about potential IQ differences between groups could restrict participants to those with IQs between 100 and 110.
• Holding a variable constant guarantees that the variable cannot confound the research, but this process limits the external validity of the research results.
![Page 15: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/15.jpg)
INDIVIDUAL DIFFERENCES AND VARIABILITY
High variability can obscure any treatment effects that may exist and therefore can undermine the likelihood of a successful study.
![Page 16: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/16.jpg)
Restricted range
40.4 50
![Page 17: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/17.jpg)
Wide Range
39.6 49.2
![Page 18: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/18.jpg)
Other threats to internal validity of between-subjects designs
• Differential attrition (Mortality) (2 Dieting Programs)
• Diffusion of treatments (communication between groups)
• Compensatory equalization (computer lab)• Compensation rivalry (John Henry)• Resentful demoralization
![Page 19: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/19.jpg)
STATISTICAL ANALYSES OF BETWEEN- SUBJECTS DESIGNS
• single- factor /two- group design or simply the two- group design
• a mean is computed for each group of participants, and then an independent- measures t-test is used to determine whether there is a significant difference between the means
![Page 20: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/20.jpg)
Advantage
• It is easy to set up a two- group study, • In addition, a two- group design provides the
best opportunity to maximize the difference between the two treatment conditions; that is, you may select opposite extreme values for the independent variable.
![Page 21: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/21.jpg)
Disadvantage of 2 groups
• The primary disadvantage of a two- group design is that it provides relatively little information. With only two groups, a researcher obtains only two real data points for comparison.
![Page 22: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/22.jpg)
Comparing Means for More Than Two Groups
• a single- factor /multiple- group design may be used. For example, a re-searcher may want to compare driving performance under three telephone conditions: while talking on a cell phone, while texting on a cell phone, and without using a phone.
![Page 23: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/23.jpg)
ANOVA
• For this study, the mean is computed for each group of participants, and a single- factor analysis of variance ( ANOVA for independent measures).
• When the ANOVA concludes that significant differences exist, some form of post hoc test or posttest is used to determine exactly which groups are significantly different from each other.
![Page 24: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/24.jpg)
Advantage of ANOVA
• In addition to revealing the full functional relationship between variables, a multiple- group design also provides stronger evidence for a real cause- and- effect relationship than can be obtained from a two- group design.
![Page 25: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/25.jpg)
Nominal and ordinal variables
• Because you cannot compute means for these variables, you cannot use an independent- measures t test or an ANOVA ( F test) to compare means between groups.
• However, it is possible to compare proportions between groups using a chi- square test for independence
![Page 26: Between- Subjects Design](https://reader035.fdocuments.net/reader035/viewer/2022062516/56812a64550346895d8ddc62/html5/thumbnails/26.jpg)
Example
Math testTeaching methods Passed failedTraditional 5 6Group Work 6 6Computer Based 4 1