Random factors in anova

By:

Jackson, Sally

Material type: Text

TextSeries: Quantitative applications in the social sciencesPublication details: Sage Publications, Inc. Beverly Hills 1994Description: 65 pISBN:

9780803950900

Subject(s):

DDC classification:

300.1519538 JAC

Summary: Description When using the analysis of variance (ANOVA) in an experimental design, how can the researcher determine whether to treat a factor as fixed or random? This book provides the reader with the criteria to make the distinction between fixed and random levels among factors, an important decision that directly reflects the purpose of the research. In addition to exploring the varied roles random factors can play in social research, the authors provide a discussion of the statistical analyses required with random factors and give an overview of computer-assisted analysis of random factor designs using SAS and SPSSX.

List(s) this item appears in: Operation & quantitative Techniques | Public Policy & General Management

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Operations Management & Quantitative Techniques	300.1519538 JAC (Browse shelf(Opens below))	1	Available		001055

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Previous	158.1 GOL The Choice	160 ZAS Quantitative reasoning:	300.11385 BRO Chaos and catastrophe theories	300.1519538 JAC Random factors in anova	300.28 MAR Analyzing panel data	300.7 GOU An introduction to systematic reviews	300.72 ASD Doing document analysis: a practice-oriented method	Next

Description
When using the analysis of variance (ANOVA) in an experimental design, how can the researcher determine whether to treat a factor as fixed or random? This book provides the reader with the criteria to make the distinction between fixed and random levels among factors, an important decision that directly reflects the purpose of the research. In addition to exploring the varied roles random factors can play in social research, the authors provide a discussion of the statistical analyses required with random factors and give an overview of computer-assisted analysis of random factor designs using SAS and SPSSX.

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