000			05515cam a2200373 a 4500
999			_c59912 _d59912
001			12497250
003			WUSLLib
005			20170712084502.0
008			010808s2001 enka b 001 0 eng c
010			_a 2001270786
020			_a0761951601
020			_a076195161X (pbk.)
035			_a(OCoLC)ocm44185265
040			_aUKM _cUKM _dTXA _dFUG _dDLC
042			_apcc
050	0	0	_aQA279 _b.R88 2001
082	0	0	_a519.538 _221 _bRUT
100	1		_aRutherford, Andrew, _d1958- _96518
245	1	0	_aIntroducing ANOVA and ANCOVA : _ba GLM approach / _cAndrew Rutherford.
260			_aLondon ; Thousand Oaks, Calif. : _bSAGE, _c2001.
300			_aix, 182 p. : _bill. ; _c25 cm.
490	1		_aIntroducing statistical methods
500			_aIndex sheets need inserting.
504			_aIncludes bibliographical references (p. [173]-177) and index.
505	8		_aMachine generated contents note: 1 AN INTRODUCTION TO GENERAL LINEAR MODELS: REGRESSION, ANALYSIS -- OF VARIANCE AND ANALYSIS OF COVARIANCE -- 1.1 Regression, analysis of variance and analysis of covariance -- 1.2 A pocket history of regression, ANOVA and ANCOVA -- 1.3 An outline of general linear models (GLMs) -- 1.3.1 Regression analysis -- 1.3.2 Analysis of variance -- 1.3.3 Analysis of covariance -- 1.4 The "general" in GLM -- 1.5 The "linear" in GLM -- 1.6 Least squares estimates -- 1.7 Fixed, random and mixed effects analyses -- 1.8 The benefits of a GLM approach to ANOVA and ANCOVA -- 1.9 The GLM presentation -- 1.10 Statistical packages for computers -- 2 TRADITIONAL AND GLM APPROACHES TO INDEPENDENT MEASURES SINGLE -- FACTOR ANOVA DESIGNS -- 2.1 Independent measures designs -- 2.1.1 Factors and independent variables -- 2.2 Traditional ANOVA for single factor designs -- 2.2.1 Variance -- 2.2.2 Example -- 2.3 GLM approaches to single factor ANOVA -- 2.3.1 Experimental design GLMs -- 2.3.2 Estimating effects by comparing full and reduced experimental -- design GLMs -- 2.3.3 Regression GLMs -- 2.3.4 Cell mean GLMs -- 2.3.5 Cell mean, regression and experimental desigh GLMs -- 3 GLM APPROACHES TO INDEPENDENT MEASURES FACTORIAL ANOVA -- DESIGNS -- 3.1 Factorial designs -- 3.2 Factor main effects and factor interactions -- 3.2.1 Estimating effects by comparing full and reduced experimental -- design GLMs -- 3.3 Regression GLMs for factorial ANOVA -- 3.3.1 Estimating main and interaction effects with regression GLMs -- 4 GLM APPROACHES TO REPEATED MEASURES DESIGNS -- 4.1 Related measures designs -- 4.2 Repeated measures designs -- 4.3 Order effect controls -- 4.3.1 Counterbalancing -- 4.3.2 Randomization -- 4.4 The GLM approach to single factor repeated measures designs -- 4.5 Estimating effects by comparing full and reduced single factor repeated -- measures design GLMs -- 4.6 Regression GLMs for single factor repeated measures designs -- 5 GLM APPROACHES TO FACTORIAL REPEATED MEASURES DESIGNS -- 5.1 Factorial related measures designs -- 5.2 The fully related factorial design GLM -- 5.3 Estimating effects by comparing full and reduced fully related factorial -- experimental design GLMs -- 5.4 Regression GLMs for the fully related factorial ANOVA -- 5.5 Mixed factorial ANOVA -- 5.6 Estimating effects by comparing full and reduced mixed factorial -- experimental design GLMs -- 5.7 Regression GLM for the mixed factorial ANOVA -- 6 THE GLM APPROACH TO ANCOVA -- 6.1 The nature of ANCOVA -- 6.2 Single factor independent measures ANCOVA designs -- 6.3 Estimating effects by comparing full and reduced single factor -- independent measures ANCOVA GLMs -- 6.4 Regression GLMs for the single factor independent measures -- ANCOVA -- 6.5 Other ANCOVA designs -- 6.5.1 Related measures ANCOVA designs -- 6.5.2 Mixed measures factorial ANCOVA -- 7 ASSUMPTIONS UNDERLYING ANOVA, TRADITIONAL ANCOVA AND GLMS -- 7.1 ANOVA and GLM assumptions -- 7.1.1 Independent measures -- 7.1.2 Related measures -- 7.1.3 Traditional ANCOVA -- 7.2 A strategy for checking ANOVA and traditional ANCOVA assumptions -- 7.3 Assumption checks and some assumption violation consequences -- 7.3.1 ANOVA and ANCOVA -- 7.3.2 Traditional ANCOVA -- 8 SOME ALTERNATIVES TO TRADITIONAL ANCOVA -- 8.1 Alternatives to traditional ANCOVA -- 8.2 The heterogeneous regression problem -- 8.3 The heterogeneous regression ANCOVA GLM -- 8.4 Single factor independent measures heterogeneous regression -- ANCOVA -- 8.5 Estimating heterogeneous regression ANCOVA effects -- 8.6 Regression GLMs for heterogeneous ANCOVA -- 8.7 Covariate-experimental condition relations -- 8.7.1 Multicollinearity -- 8.8 Other alternatives -- 8.8.1 Stratification (blocking) -- 8.8.2 Replacing the experimental conditions with the covariate -- 8.9 The role of ANCOVA -- 9 FURTHER ISSUES IN ANOVA AND ANCOVA -- 9.1 Power -- 9.1.1 Optimal experimental designs -- 9.1.2 Normality violations -- 9.1.3 Main effects and interactions -- 9.2 Error rate and the omnibus F-tests -- 9.3 Error rate and multiple comparisons -- 9.4 The role of the omnibus F-test -- REFERENCES -- INDEX.
650		0	_aAnalysis of variance. _96519
650		0	_aAnalysis of covariance. _96520
830		0	_aISM (London, England) _96521
856	4		_3Table of Contents only _uhttp://www.loc.gov/catdir/toc/fy02/2001270786.html
856	4	2	_3Publisher description _uhttp://www.loc.gov/catdir/enhancements/fy0656/2001270786-d.html
906			_a7 _bcbc _cpccadap _d2 _encip _f20 _gy-gencatlg
942			_2ddc _cSR