Applied Medical Statistics Using SAS

539 Pages·2012·3.899 MB·\539

by  Geoff Der (Author), Brian S. Everitt (Author)

Applied Medical
Statistics Using SAS

Applied Medical
Statistics Using SAS
Geoff Der
Brian S. Everitt
CRC Press
Taylor & Francis Group
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Contents
Preface ...................................................................................................................xiii
The Authors ...........................................................................................................xv
1. An Introduction to SAS .................................................................................1
1.1 Introduction ...........................................................................................1
1.2 User Interface .........................................................................................1
1.2.1 Editor Window .........................................................................2
1.2.2 Log Window .............................................................................4
1.2.3 Output Window .......................................................................4
1.2.4 Results Window .......................................................................4
1.2.5 Explorer Window .....................................................................4
1.2.6 Results Viewer Window ..........................................................5
1.2.7 Options for Displaying Procedure Results ..........................5
1.2.8 Help and Documentation .......................................................5
1.3 SAS Programs ........................................................................................6
1.3.1 Program Steps ..........................................................................7
1.3.2 Variable Names and Data Set Names ...................................8
1.3.3 Variable Lists ............................................................................8
1.4 Reading Data—The Data Step ...........................................................11
1.4.1 Creating SAS Data Sets from Raw Data .............................11
1.4.2 Data Statement .......................................................................11
1.4.3 Infile Statement ......................................................................12
1.4.4 Input Statement ......................................................................13
1.4.4.1 List Input .................................................................13
1.4.4.2 Column Input ..........................................................14
1.4.4.3 Formatted Input......................................................15
1.4.4.4 Multiple Lines per Observation ...........................17
1.4.4.5 Multiple Observations per Line ...........................17
1.4.4.6 Delimited Data .......................................................17
1.4.5 Reading Data—Proc Import .................................................18
1.4.6 Reading and Writing Excel Files..........................................19
1.4.7 Temporary and Permanent SAS Data Sets—SAS
Libraries...................................................................................20
1.4.8 Reading Data from an Existing SAS Data Set....................20
1.5 Modifying SAS Data ...........................................................................21
1.5.1 Creating and Modifying Variables ......................................21
1.5.1.1 Missing Values in Arithmetic Expressions ........21
1.5.2 Deleting Variables ..................................................................24
1.5.3 Deleting Observations ..........................................................24
1.5.4 Subsetting Data Sets ..............................................................24
v
vi Contents
1.5.5 Concatenating and Merging Data Sets ...............................25
1.5.6 Merging Data Sets—Adding Variables ...............................25
1.5.7 Operation of the Data Step ...................................................26
1.6 Proc Step ...............................................................................................27
1.6.1 Proc Statement ........................................................................27
1.6.2 Var Statement ..........................................................................27
1.6.3 Where Statement ....................................................................28
1.6.4 By Statement ...........................................................................28
1.6.5 Class Statement ......................................................................28
1.7 Global Statements................................................................................28
1.7.1 Options ....................................................................................29
1.8 SAS Graphics........................................................................................30
1.8.1 xy Plots—proc sgplot ........................................................30
1.8.2 Summary Plots .......................................................................31
1.8.3 Panel Plots ...............................................................................32
1.9 ODS—Output Delivery System ........................................................32
1.9.1 ODS Procedure Output .........................................................33
1.9.1.1 ODS Styles ...............................................................33
1.10 Saving Output in SAS Data Sets—ods output .............................34
1.10.1 ODS Graphics .........................................................................34
1.11 Enhancing Output ..............................................................................36
1.11.1 Variable Labels .......................................................................36
1.11.2 Value Labels—SAS Formats .................................................36
1.12 SAS Macros ..........................................................................................37
1.13 Some Tips for Preventing and Correcting Errors ...........................39
2. Statistics and Measurement in Medicine ................................................41
2.1 Introduction .........................................................................................41
2.2 A Brief History of Medical Statistics ................................................42
2.3 Measurement in Medicine .................................................................46
2.3.1 Scales of Measurement ..........................................................47
2.3.1.1 Nominal or Categorical Measurements ..............47
2.3.1.2 Ordinal Scale Measurements ...............................47
2.3.1.3 Interval Scales .........................................................48
2.3.1.4 Ratio Scales ..............................................................48
2.4 Assessing Bias and Reliability of Measurements ...........................49
2.4.1 Assessing Reliability and Bias for Binary and Other
Categorical Observations ......................................................50
2.4.2 Assessing the Reliability of Quantitative Measurements ...57
2.5 Diagnostic Tests ...................................................................................63
2.6 Summary ..............................................................................................72
3. Clinical Trials ................................................................................................73
3.1 Introduction .........................................................................................73
Contents vii
3.2 Clinical Trials .......................................................................................74
3.2.1 Types of Randomisation .......................................................77
3.2.1.1 Blocked Randomisation ........................................80
3.2.1.2 Stratified Randomisation ......................................82
3.2.1.3 Minimisation Method ...........................................85
3.3 How Many Participants Do I Need in My Trial? ............................88
3.4 Analysis of Data from Clinical Trials ...............................................92
3.4.1 p-Values and Confidence Intervals ......................................92
3.4.2 Some Examples of Analysis of Data from Clinical
Trials Using Familiar Statistical Methods ..........................94
3.5 Summary ............................................................................................107
4. Epidemiology ...............................................................................................109
4.1 Introduction .......................................................................................109
4.2 Types of Epidemiological Study .....................................................109
4.2.1 Surveys ..................................................................................110
4.2.2 Case-Control Studies ...........................................................111
4.2.3 Cohort Studies ......................................................................112
4.3 Relative Risk and Odds Ratios ........................................................114
4.4 Sample Size Estimation for Epidemiologic Studies .....................116
4.4.1 Sample Size Estimation for Case-Control Studies ..........116
4.4.2 Sample Size Estimation for Cohort Studies .....................118
4.5 Simple Analyses for Data from Observational Studies ...............119
4.5.1 Chi-Squared Test for Association ......................................119
4.5.2 Finding a Confidence Interval for the Relative Risk
and the Odds Ratio ..............................................................120
4.5.3 Applying SAS to Analyse Examples of
Epidemiological Data ..........................................................121
4.5.4 Fisher’s Test ...........................................................................125
4.5.5 Matched Case-Control Data ...............................................128
4.5.6 Stratified 2 × 2 Tables ...........................................................129
4.6 Summary ............................................................................................132
5. Meta-Analysis .............................................................................................135
5.1 Introduction .......................................................................................135
5.2 Study Selection ..................................................................................138
5.3 Publication Bias .................................................................................140
5.4 Statistics of Meta-Analysis ...............................................................141
5.4.1 Fixed-Effects Model .............................................................143
5.4.2 Random-Effects Model ........................................................143
5.5 An Example of the Application of Meta-Analysis ........................144
5.6 Meta-Analysis on Sparse Data ........................................................150
5.7 Meta-Regression ................................................................................152
5.8 Summary ............................................................................................155
viii Contents
6. Analysis of Variance and Covariance ....................................................157
6.1 Introduction .......................................................................................157
6.2 A Simple Example of One-Way Analysis of Variance .................157
6.2.1 One-Way Analysis of Variance Model ..............................158
6.2.2 Applying the One-Way Analysis of Variance Model
to Sickle Cell Disease Data .................................................159
6.3 Multiple Comparison Procedures...................................................162
6.3.1 Planned Comparisons .........................................................162
6.3.2 Post Hoc Comparisons ........................................................164
6.4 A Factorial Experiment ....................................................................165
6.4.1 Model for Three-Factor Design ..........................................170
6.5 Unbalanced Designs .........................................................................172
6.5.1 Type I Sums of Squares .......................................................174
6.5.2 Type II Sums of Squares .....................................................174
6.5.3 Type III Sums of Squares ....................................................175
6.5.4 Analysis of Antipyrine Data ..............................................176
6.6 Nonparametric Analysis of Variance .............................................178
6.6.1 Kruskal–Wallis Distribution-Free Test for One-Way
Analysis of Variance ............................................................179
6.6.2 Applying the Kruskal–Wallis Test ....................................180
6.7 Analysis of Covariance ....................................................................181
6.8 Summary ............................................................................................186
7. Scatter Plots, Correlation, Simple Regression, and Smoothing........187
7.1 Introduction .......................................................................................187
7.2 Scatter Plot and Correlation Coefficient ........................................187
7.3 Simple Linear Regression and Locally Weighted Regression ....193
7.4 Locally Weighted Regression ..........................................................203
7.5 Aspect Ratio of a Scatter Plot ..........................................................205
7.6 Estimating Bivariate Densities ........................................................209
7.7 Scatter Plot Matrices .........................................................................213
7.8 Summary ............................................................................................216
8. Multiple Linear Regression ......................................................................219
8.1 Introduction .......................................................................................219
8.2 Multiple Linear Regression Model .................................................219
8.3 Some Examples of the Application of the Multiple
Linear Regression Model .................................................................222
8.3.1 Effect of the Amount of Anaesthetic Agent
Administered during an Operation ..................................222
8.3.2 Mortality and Water Hardness ..........................................224
8.3.3 Weight and Physical Measurements in Men ...................230
8.4 Identifying a Parsimonious Model .................................................235
8.4.1 All Possible Subsets Regression .........................................235
8.4.2 Stepwise Methods ................................................................236
Contents ix
8.5 Checking Model Assumptions: Residuals and Other
Regression Diagnostics ....................................................................245
8.6 General Linear Model .......................................................................249
8.7 Summary ............................................................................................253
9. Logistic Regression ....................................................................................255
9.1 Introduction .......................................................................................255
9.2 Logistic Regression ...........................................................................255
9.3 Two Examples of the Application of Logistic Regression ...........258
9.3.1 Psychiatric ‘Caseness’ ..........................................................258
9.3.2 Birth Weight of Babies .........................................................268
9.4 Diagnosing a Logistic Regression Model ......................................274
9.5 Logistic Regression for 1:1 Matched Studies .................................275
9.6 Propensity Scores ..............................................................................281
9.7 Summary ............................................................................................283
10. Generalised Linear Model ........................................................................285
10.1 Introduction .......................................................................................285
10.2 Generalised Linear Models .............................................................285
10.3 Applying the Generalised Linear Model .......................................287
10.3.1 Poisson Regression ..............................................................288
10.3.2 Regression with Gamma Errors ........................................296
10.4 Residuals for GLMs ..........................................................................298
10.5 Overdispersion ..................................................................................300
10.6 Summary ............................................................................................302
11. Generalised Additive Models ..................................................................303
11.1 Introduction .......................................................................................303
11.2 Scatter Plot Smoothers ......................................................................304
11.3 Additive and Generalised Additive Models .................................312
11.4 Examples of the Application of GAMs ..........................................313
11.5 Summary ............................................................................................324
12. Analysis of Longitudinal Data I ..............................................................325
12.1 Introduction .......................................................................................325
12.2 Graphical Displays of Longitudinal Data ......................................325
12.3 Summary Measure Analysis of Longitudinal Data .....................333
12.3.1 Choosing Summary Measures ..........................................333
12.3.2 Applying the Summary Measure Approach ...................334
12.3.3 Incorporating Pretreatment Outcome Values into
the Summary Measure Approach .....................................335
12.3.4 Dealing with Missing Values When Using
the Summary Measure Approach .....................................337
12.4 Summary Measure Approach for Binary Responses ..................340
12.5 Summary ............................................................................................347