Understanding and Using Advanced Statistics: A Practical Guide for Students

193 Pages·2005·0.824 MB·English

by  Jeremy J Foster, Emma Barkus, Christian Yavorsky

UNDERSTANDING
AND
USING ADVANCED STATISTICS
Jeremy J Foster
Emma Barkus
Christian Yavorsky
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UNDERSTANDING AND
USING ADVANCED STATISTICS
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UNDERSTANDING AND
USING ADVANCED STATISTICS
Jeremy Foster
Emma Barkus
Christian Yavorsky
SAGE Publications
London ●Thousand Oaks ● New Delhi
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© Jeremy Foster,Emma Barkus,Christian Yavorsky 2006
First published 2006
Apart from any fair dealing for the purposes of
research or private study,or criticism or review,as
permitted under the Copyright,Designs and Patents Act,
1988,this publication may be reproduced,stored or
transmitted in any form,or by any means,only with
the prior permission in writing of the publishers,
or in the case of reprographic reproduction,in accordance
with the terms of licences issued by the Copyright Licensing
Agency.Enquiries concerning reproduction outside those
terms should be sent to the publishers.
SAGE Publications Ltd
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SAGE Publications India Pvt Ltd
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BBrriittiisshh LLiibbrraarryy CCaattaalloogguuiinngg iinn PPuubblliiccaattiioonn ddaattaa
A catalogue record for this book is available from the
British Library
ISBN 1 4129 0013 1
ISBN 1 4129 0014 X (pbk)
LLiibbrraarryy ooff CCoonnggrreessss CCoonnttrrooll NNuummbbeerr:: 22000055992299118800
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Printed on paper from sustainable resources
Printed in Great Britain by The Cromwell Press Ltd,Trowbridge,Wiltshire
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Summary of Contents
1 Basic features of statistical analysis and the general linear model 1
2 Multivariate analysis of variance 16
3 Multiple regression 30
4 Log–linear analysis 47
5 Logistic regression 57
6 Factor analysis 70
7 Path analysis 89
8 Structural equation modelling 103
9 Time series analysis 115
10 Facet theory and smallest space analysis 130
11 Survival or failure analysis 145
12 Repertory grids 156
Index 173
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Contents
11 BBaassiicc ffeeaattuurreess ooff ssttaattiissttiiccaall aannaallyyssiiss aanndd tthhee ggeenneerraall lliinneeaarr mmooddeell 11
Introduction 1
Basic features of statistical analysis 2
Experiments or correlational research designs 2
Independent and dependent variables 2
Types of data 3
Non-parametric and parametric analyses 4
Statistical significance 6
Recapitulation of analysis of variance (ANOVA) 7
Main effects,simple effects,interaction 8
The general linear model 10
When do you need the GLM? 11
Summary 13
Glossary 14
References 14
Further reading 14
Internet sources 15
22 MMuullttiivvaarriiaattee aannaallyyssiiss ooff vvaarriiaannccee 1166
What multivariate analysis of variance is 16
When do you need MANOVA? 16
What kinds of data are necessary? 16
How much data? 17
Example of MANOVA 17
What a MANOVA does 19
Example of output of SPSS 22
Example of the use of MANOVA 26
From health 26
FAQs 27
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viii • CONTENTS
Summary 28
Glossary 28
References 28
Further reading 29
Internet sources 29
33 MMuullttiippllee rreeggrreessssiioonn 3300
What multiple regression is 30
When do you need multiple regression? 30
Words of warning 31
Recapitulation of correlation and regression 31
Recapitulation of partial correlation 32
The regression equation in multiple regression 33
What kinds of data are needed? 35
How much data? (How many respondents for how many
independent variables?) 35
Which independent variables to include? 36
Technical considerations and screening the data 36
Outliers 36
Muticollinearity 37
Normally distributed,linearly related,homoscedastic? 38
How do you do multiple regression? 39
Cross-validation 41
Interactions 41
Examples of multiple regression and its interpretation 42
From psychology 42
From health 42
From business/management 43
FAQs 44
Summary 44
Glossary 45
References 45
44 LLoogg––lliinneeaarr aannaallyyssiiss 4477
What log–linear analysis is 47
Recapitulation of contingency tables 47
When do you need log–linear analysis? 49
What kinds of data are needed? 49
How much data? 49
How to do log–linear analysis 49
Examples from psychology,health and business 52
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Contents • ix
From psychology 52
From health 54
From business 54
FAQs 55
Summary 55
Glossary 56
References 56
Further reading 56
55 LLooggiissttiicc rreeggrreessssiioonn 5577
What logistic regression is 57
When do you need logistic regression? 57
Different types of logistic regression 59
What kinds of data are needed? 62
How much data? (How many respondents for how many
independent variables?) 62
Which independent variables to include? 62
Technical considerations and screening the data 62
How do you do logistic regression? 63
Limitations of logistic regression 63
Example of logistic regression and its interpretation 64
Examples of the use of logistic regression 67
From psychology 67
From health 68
FAQs 68
Summary 68
Glossary 69
References 69
Further reading 69
Internet source 69
66 FFaaccttoorr aannaallyyssiiss 7700
What factor analysis is 70
When do you need factor analysis? 70
Principal components analysis and factor analysis 71
What kinds of data are needed? 72
How much data? (How many respondents for how many
independent variables?) 73
How many variables to include? 74
Which variables to include? 74
Technical considerations and screening the data 75