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UNIVERSITY OF SOUTHERN QUEENSLAND
AN INVESTIGATION OF THE EXISTENCE OF DISTINCTIVE MMPI-2 PROFILESIN THREE DIAGNOSTICALLY DIFFERENT FORENSIC SAMPLES
A dissertation submitted by
Warren BakerB.App.Sc (Psych), B.Sc, Hons (Psych)
For the award of
Doctor of Philosophy
2006
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CERTIFICATION OF DISSERTATION
I certify that the ideas, experimental work, results, analysis, and conclusions reported inthis dissertation are my own effort, except where otherwise acknowledged. I also certifythat the work is original and has not been previously submitted for any other award,except where otherwise acknowledged.
Warren Baker Date:
ENDORSEMENT
Dr. Graeme Senior (Supervisor) Date:
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TABLE OF CONTENTS
Page
CERTIFICATION OF DISSERTATION i
APPENDICES viii
LIST OF TABLES ix
LIST OF FIGURES xiii
ACKNOWLEDGEMENTS xvi
ABSTRACT xvii
CHAPTER ONECurrent Issues with the Interpretation of MMPI-2 Group Profiles
1.1 Overview 1
1.2 Forensic use of the MMPI-2 1
1.3 Issues in Group Classification 14
1.4 The Need for more Complex Strategies 14
1.5 Aim of the Current Investigation 17
CHAPTER TWOCluster Analysis: A Method to Examine the Existence of Clinical Subgroups inForensic Samples
2.1 Overview 19
2.2 Background 19
2.3 Essential Issues in Cluster analysis 20
2.4 Sample Selection 21
2.5 Definition of Variables with which to Measure Subjects in the Sample 21
2.6 Standardisation of Data 23
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CHAPTER TWO (Continued)
Page
2.7 Detection of Outliers 25
2.8 Selection of a Method of Cluster Analysis 26
2.8.1 Hierarchical Clustering Procedures 262.8.2 Hierarchical Agglomerative 27
2.8.2.1 Single Linkage 282.8.2.2 Complete Linkage 282.8.2.3 Average Linkage 292.8.2.4 Wards Method 29
2.8.3 Hierarchical Divisive 302.8.4 Iterative Partitioning 302.8.5 Factor Analysis 31
2.9 Comparison of Cluster Analysis Studies 32
2.10 Computation of Similarity / Dissimilarity 342.10.1 Proximity Measures 34
2.10.1.1 Correlation Coefficient 352.10.1.2 Euclidean Distance 352.10.1.3 Squared Euclidean Distance 36
2.11 The Role of Shape, Elevation and Scatter in MMPI-2 36Profiles
2.12 Determination of the Number of Clusters 372.12.1 Dendrograms 382.12.2 Icicle Plots 392.12.3 Inverse Scree Plots 392.12.4 Stopping Rules 40
2.13 Summary 41
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CHAPTER THREEThe MMPI-2 and Chronic Pain Page
3.1 Overview 44
3.2 The Need for Classification 44
3.3 Classification Approaches 45
3.4 Review of Previous MMPI-2 Cluster Analytic Research 46
3.5 Summary 52
CHAPTER FOURCluster Analysis of a Forensic Chronic Pain Sample
4.1 Overview 53
4.2 Method 53
4.2.1 Subjects 534.2.2 Measures 554.2.3 Data Screening 55
4.3 Analysis and Results 56
4.4 Hierarchical Cluster Analysis Results 58
4.4.1 Hierarchical Cluster 1 594.4.2 Hierarchical Cluster 2 594.4.3 Hierarchical Cluster 3 61
4.5 Comparison of Clusters with Previous 61Studies of Mixed Pain Samples
4.6 Comparison of Clusters with Previous Research 65of Low Back Pain Samples
4.7 K-means Cluster Analysis 65
4.7.1 k-means Cluster 1 704.7.2 k-means Cluster 2 764.7.3 k-means Cluster 3 80
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CHAPTER FOUR (Continued)Page
4.8 General Summary and Conclusion 83
CHAPTER FIVECluster Analysis of a Forensic Traumatic Brain Injury Sample
5.1 Overview 85
5.2 Method 86
5.2.1 Subjects 865.2.2 Measures 875.2.3 Data Screening 885.2.4 Scale Base Rates 88
5.3 Analysis and Results 88
5.4 k-means Cluster Analysis 90
5.5 k-means Cluster Solutions 91
5.5.1 k-means Cluster 1 915.5.2 k-means Cluster 2 975.5.3 k-means Cluster 3 1005.5.4 k-means Cluster 4 103
5.6 General Summary and Conclusion 106
CHAPTER 6Cluster Analysis of a Forensic Post Traumatic Stress Disorder Sample
6.1 Overview 107
6.2 Method 108
6.2.1 Subjects 1086.2.2 Measures 1106.2.3 Data Screening 1106.2.4 Scale Base Rates 111
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CHAPTER SIX (Continued)Page
6.3 Analysis and Results 1116.4 k-means Cluster Analysis 113
6.4.1 k-means Cluster 1 1146.4.2 k-means Cluster 2 1196.4.3 k-means Cluster 3 123
6.5 General Summary and Conclusion 124
CHAPTER 7Comparison of Diagnostic Group Profiles
7.1 Overview 127
7.2 Graphic Comparisons 131
7.2.1 Within Normal Limits Profiles 1317.2.2 High Distress Profiles 1347.2.3 High Distress / High Disturbance Profiles 134
CHAPTER 8Cluster Analysis of the Combined CP, TBI, and PTSD Samples
8.1 Combined Forensic Sample Cluster Analysis Results 141
8.2 k-means Cluster Analysis Results 142
8.3 Scale Base Rates 144
8.3.1 k-means Cluster 1 1448.3.2 k-means Cluster 2 1518.3.3 k-means Cluster 3 1528.3.4 k-means Cluster 4 158
8.4 Diagnostic Distribution Across the Four Clusters 159
8.5 Summary and Conclusion 162
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CHAPTER 9General Discussion, and Implications for Clinical Practice Page
9.1 Overview 164
9.2 General Discussion and Summary of Results 165
9.2.1 Study One 1669.2.2 Study Two 1679.2.3 Study Three 1689.2.4 Study Four 1699.2.5 Study Five 169
9.3 Conclusions 170
9.4 Limitations 171
9.5 Conclusion and Implications for Clinical Practice 173
REFERENCES 176
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APPENDICES
Page
Appendix A Mean Validity, Clinical, and Content Scale Scores 187for the Hierarchical (h) CP Cluster Solutions
Appendix B Mean Validity, and Clinical Scale Scores 188for the k-means (k) CP Cluster Solutions
Appendix C Mean Content Scale Scores for the k-means (k) 190CP Cluster Solutions
Appendix D Mean Validity, Clinical, and Content Scale Scores 192for the Hierarchical (h) TBI Cluster Solutions
Appendix E Mean Validity, and Clinical Scores for the k-means 193TBI Cluster Solutions
Appendix F Mean Content Scale Score for the k-means (k) 195TBI Cluster Solutions
Appendix G Mean Validity, Clinical, and Content Scale Scores 197for the Hierarchical (h) PTSD Cluster Solutions
Appendix H Mean Validity, and Clinical Scores for the k-means 198PTSD Cluster Solutions
Appendix I Mean Content Scale Score for the k-means (k) 200PTSD Cluster Solutions
Appendix J Mean Validity, Clinical, and Content Scale Scores 202for the Hierarchical (h) Combined Sample Cluster Solutions
Appendix K Mean Validity, and Clinical Scores for the k-means 203Combined Sample Cluster Solutions
Appendix L Mean Content Scale Score for the k-means (k) 205Combined Sample Cluster Solutions
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LIST OF TABLES
Table Page
1.1 MMPI-2 Validity Scales 4
1.2 MMPI-2 Clinical Scales and Subscales 7
1.3 MMPI-2 Content Scales and Subscales 10
1.4 The Restructured Clinical (RC) Scales 12
4.1 Characteristics of the Forensic Chronic Pain Group 54
4.2 Percentage change in the Agglomeration Coefficient 58for the Hierarchical Cluster Analysis
4.3 Mean Clinical Scale Scores for the k-means 69Cluster Solutions
4.4 Correlations between Chronic Pain k-means clusters 70
4.5 Percentages of Elevations =>65 of CP Cluster 1 74Clinical Scale and Subscales
4.6 Percentages of Elevations =>65 of the CP Cluster 1 75Content Scale and Subscales
4.7 Percentages of Elevations =>65 of the CP Cluster 2 78Clinical Scale and Subscales
4.8 Percentages of Elevations =>65 of the CP Cluster 2 79Content Scale and Subscales
4.9 Percentages of Elevations =>65 of the CP Cluster 3 81Clinical Scale and Subscales
4.10 Percentages of Elevations =>65 of the CP Cluster 3 82Content Scale and Subscales
5.1 Characteristics of the Forensic Traumatic Brain Injury 87Group
5.2 Percentage Change in the Agglomeration Coefficient 89for the TBI Hierarchical Cluster Analysis
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LIST OF TABLES (Continued)
Table Page
5.3 Mean Clinical Scale Scores for the k-means TBI Cluster Solutions 90
5.4 Correlations between TBI k-means clusters 91
5.5 Percentages of Elevations =>65 of the TBI Cluster 1 95Clinical Scale and Subscales
5.6 Percentages of Elevations =>65 of the TBI Cluster 1 96Content Scale and Subscales
5.7 Percentages of Elevations =>65 of the TBI Cluster 2 98Clinical Scale and Subscales
5.8 Percentages of Elevations =>65 of the TBI Cluster 2 99Content Scale and Subscales
5.9 Percentages of Elevations =>65 of the TBI Cluster 3 101Clinical Scale and Subscales
5.10 Percentages of Elevations =>65 of the TBI Cluster 3 102Content Scale and Subscales
5.11 Percentages of Elevations =>65 of k-means TBI Cluster 4 104Clinical Scale and Subscales
5.12 Percentages of Elevations =>65 of the TBI Cluster 4 105Content Scale and Subscales
6.1 Characteristics of the Forensic PTSD Sample 110
6.2 Percentage Change in the Agglomeration Coefficient 112for the Hierarchical Cluster Analysis
6.3 Mean Clinical Scale Scores for the k-means Cluster Solutions 113
6.4 Correlations between PTSD k-means clusters 114
6.5 Percentage of Elevations => 65 of k-means PTSD 117Cluster 1 Clinical Scales and Subscales
6.6 Percentage of Elevations => 65 of k-means PTSD 118Cluster 1 Content Scales and Subscales
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LIST OF TABLES (Continued)
Table Page
6.7 Percentage of Elevations => 65 of k-means PTSD 121Cluster 2 Clinical Scales and Subscales
6.8 Percentage of Elevations => 65 of k-means PTSD 122Cluster 2 Content Scales and Subscales
6.9 Percentage of Elevations => 65 of k-means PTSD 124Cluster 3 Clinical Scales and Subscales
6.10 Percentage of Elevations => 65 of k-means PTSD 125Cluster 3 Content Scales and Subscales
7.1 Correlations between Diagnostic Group Profiles 130
8.1 Percentage Change in the Agglomeration Coefficient 142For the Combined Sample Hierarchical Analysis
8.2 Mean MMPI-2 Scores for the k-means Cluster Solutions 143
8.3 Correlations between Combined Sample k-means Clusters 144
8.4 Percentage of cases that Elevated Response Bias Scales 146
8.5 Percentage of Elevations of Clinical Scale and Subscale 147scores for Cluster 1
8.6 Percentage of Elevations of Content Scale and Subscale 148scores for Cluster 1
8.7 Percentage of Elevations of Clinical Scale and Subscale 153scores for Cluster 2
8.8 Percentage of Elevations of Content Scales and Subscale 154scores for Cluster 2
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LIST OF TABLES (Continued)
Table Page
8.9 Percentage of Elevations of Clinical Scales and Subscale 156scores for Cluster 3
8.10 Percentage of Elevations of Content Scales and Subscale 157scores for Cluster 3
8.11 Percentage of Elevations of Clinical Scales and Subscale 160scores for Cluster 4
8.12 Percentage of Elevations of content Scale and Subscale 161scores for Cluster 4
8.13 Distribution of Diagnostic Groups by k-means Cluster 162
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LIST OF FIGURES
Figure Page
1.1 Examples of WNL, HDs / LDb, HDs / HDs Profiles 5
1.2 Examples of most frequently occurring Neurotic 6Triad configurations
2.1 Example of a Dendrogram 38
2.2 Example of an Icicle Plot 39
2.3 Example of an Inverse Scree Plot 40
3.1 Mean Validity and Basic Scale T-scores by Hierarchical 48Cluster Group from Riley et al. (1993)
3.2 Mean Validity and Basic Scale T-scores by Hierarchical 48Cluster Group from Riley & Robinson (1998)
3.3 Mean Validity and Basic Scale T-scores by Hierarchical 50Cluster Group for Males from Keller & Butcher (1991)
3.4 Mean Content Scale T-scores by Hierarchical 50Cluster Group for females from Keller & Butcher (1991)
4.1 Inverse Scree Plot of the Final 50 CP Agglomeration 57Coefficients
4.2 Mean Validity and Clinical Scale T-scores by 60Hierarchical Cluster Group
4.3 Mean Scores for the Within Normal Limits 62
4.4 Mean Scores for the High Distress / Low Disturbance Profiles 63
4.5 Mean Scores for the High Distress / High Disturbance Profiles 65
4.6 Mean Scores for the Within Normal Limits Profiles 66
4.7 Mean Scores for High Distress / Low Disturbance Profiles 67
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LIST OF FIGURES (continued)
Figure Page
4.8 Mean Scores for High Distress / High Disturbance Profiles 68
4.9 Mean Validity and Clinical Scale T-scores by 71k-means Cluster
4.10 Mean Content Scale T-scores by k-means 72Cluster
5.1 Inverse Scree Plot of the Final 50 TBI Agglomeration Coefficients 89
5.2 Mean Clinical Scale T-scores by k-means Cluster 92
5.3 Mean Content Scale T-scores by k-means Cluster 93
6.1 Inverse Scree Plot of the Final 50 PTSD Agglomeration 111Coefficients
6.2 Mean Validity and Clinical Scale Scores 115by k-means Cluster
6.3 Mean Content Scale Scores by k-means cluster 116
7.1a Comparison of Within Normal Limits Clusters – Validity 132and Clinical Scales
7.1b Comparison of Within Normal Limits Clusters – Content 133Scales
7.2a Comparison of High Distress / Low Disturbance Clusters 135Validity and Clinical Scales
7.2b Comparison of High Distress / Low Disturbance Clusters 136Content Scales
7.3a Comparison of High Distress / High Disturbance – Validity 137and Clinical Scales
7.3b Comparison of High Distress / High Disturbance – Content 138Scales
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LIST OF FIGURES (continued)
Figure Page
8.1 Inverse Scree Plot of the final 50 Agglomeration 141Coefficients of the Combined Sample
8.2 Mean K-corrected T-scores for the Clinical Scales 149
8.3 Mean K-corrected T-scores for the Content Scales 150
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ACKNOWLEDGEMENTS
I would like to express my appreciation to my supervisor, Dr Graeme Senior for
his time, and advice during the course of my PhD candidature. Thanks must also go to
the clinicians who provided access to the MMPI-2 data. Without their willingness to
provide this information, the goals of the project would not have been achieved. Further
thanks must go the USQ technical staff, Sarah, Sammy, and Ross, for their assistance
during the course of my candidature. Thanks also, to my PhD compatriots, Rael, David,
Majella, and Charmane for their friendship, support, scholarly advice, and numerous
hangovers. To my wife Bernadette, and daughters Sarah, Katherine, and Anna, thank you
for your patience, love, and support.
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ABSTRACT
Medico-legal examination of people who have suffered physical or psychological
injuries usually involves the assessment of psychological adjustment post-injury. An
assumption that appears prevalent in the research literature, is that individuals with the
same organic or psychological disorders will form relatively homogeneous groups, and
hence exhibit similar patterns of test performance. In essence this assumption underlies
the notion that clinical group means accurately reflect the behaviour of the individuals
that constitute different diagnostic groups.
Four studies were undertaken in this study. The first study examined the cluster
patterns of MMPI-2 test performance in a medico-legal sample (n = 197) of individuals
suffering Chronic Pain. Study two investigated MMPI-2 cluster patterns in a medico-
legal sample of individuals (n = 200) who had suffered a Traumatic Brain Injury. The
third study examined distinctive MMPI-2 cluster profiles in a medico-legal sample of
individuals (n = 132) suffering Post Traumatic Stress Disorder. The final study
compared the results of the previous investigations to determine whether there was any
communality in the cluster profiles found in the three diagnostically different samples.
Both hierarchical (Ward’s Method), and k-means cluster analysis procedures were
employed to identify the number of clusters, and common patterns of MMPI-2 test
performance in the three aforementioned forensic samples.
Results indicated that multiple profiles (three to four) exist within the each of the
three different diagnostic groups. The profiles, however, indicated that a single pattern of
MMPI-2 performance does not appear to be characteristic of a particular disorder. The
notion of homogeneity of test patterns (as far as the MMPI-2 is concerned) within a
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diagnostic group was not supported. The MMPI-2 profiles identified in each of the
clinical classifications were not found to be specific to these forensic samples, and
commonly occurred across the three diagnostic groups.
Cluster analysis appeared to be a useful methodology to determine commonly
occurring profiles within a specified population. A considerable number of elevated
responses, however, were noted for the Within Normal Limits (WNL) profiles. This
classification may be somewhat of a misnomer, due to high numbers of individuals still
indicating difficulties. The current findings highlight the complexity of attempting to
classify individual patterns of MMPI-2 test performance in terms of a single diagnostic
category, and directly challenge the utility of the MMPI-2 as an effective tool in this
regard.