Statistics for clinicians: how much should a doctor know?
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| Beschreibung: | xl, 610 Seiten Diagramme |
| ISBN: | 9783031207570 |
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Datensatz im Suchindex
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| adam_text | Contents 1 Expressing and Analyzing Variability.......................................... 1.1 Introduction............................................................................... 1.2 Variables: Types, Measurement and Role.............................. 1.2.1 Variable Conversion................................................. 1.3 Summarizing Data.................................................................... 1.3.1 The Qualitative Variable........................................... 1.3.2 The Quantitative Variable........................................ 1.3.3 Measures of Central Tendency................................ 1.3.4 Measures of Dispersion............................................. 1.4 The Normal Distribution........................................................... 1.4.1 The Standardized Normal Distribution and the Z Score......................................................... 1.4.2 The Confidence Interval (CI).................................... 1.4.3 Verifying Normality................................................... 1.4.4 Normalization of Data............................................... 1.5 The P-value.............................................................................. 1.5.1 The Primary Risk of Error (a).................................. 1.6 The Null and Alternative Hypothesis..................................... 1.6.1 Statistical Significance and the Degree of Significance............................................................ 1.7 Testing Hypothesis................................................................... 1.7.1 A
Simple Parametric Test......................................... 1.7.2 Unilateral Study Design............................................. 1.7.3 Bilateral Study Design................................................ 1.7.4 The Secondary Risk of Error..................................... 1.8 Common Indices of Clinical Outcomes.................................. 1.8.1 The Risk and the Odds.............................................. 1.8.2 The Relative Risks and the Odds Ratio................... 1.8.3 The Hazard Ratio...................................................... 1.8.4 Relative Risk Increase (RRI) and Relative Risk Reduction (RRR).............................................. 1.8.5 Absolute Risk Increase (ARI) and Reduction (ARR)......................................................................... 1.8.6 Number Needed to Treat Benefit (NNTB) and Number Needed to Harm (NNTH).................. 1.8.7 Calculation of the 95% Confidence Interval 51 and Testing Statistical Significance.......... 1 1 2 2 3 4 7 7 7 10 12 15 25 30 31 31 32 34 34 34 34 36 37 39 39 39 43 49 50 50 XV
Contents xvi Diagnostic Accuracy................................................................. 1.9.1 The Discriminative Measures.................................... 1.9.2 The Predictive Values............................................... 1.9.3 The Likelihood Ratios................................................ 1.9.4 Single Indicators of Test Performance..................... 1.9.5 Choosing the Appropriate Diagnostic Test.............. 1.9.6 Comparing Two Diagnostic Tests............................ 1.9.7 The Standards for Reporting Diagnostic Accuracy (STARD)..................................... References............................................................................................. 1.9 2 56 57 63 66 71 82 83 85 85 Bivariate Statistical Analysis............................................................ 87 2.1 Choosing a Statistical Test..................................................... 88 2.1.1 Independence of Data: Paired Versus Unpaired Tests............................................. 89 2.1.2 Data Distribution: Parametric Versus Distribution-Free Tests................................ 89 2.2 Consulting Statistical Tables.................................................... 90 2.2.1 The Test Statistics...................................................... 90 2.2.2 The Degrees of Freedom (Df)................................... 91 2.2.3 Consulting IndividualTables...................................... 93 2.3 Inferences on Two Qualitative Variables.............................. 97 2.3.1 The Unpaired
Tests.................................................... 97 2.3.2 The Paired Tests........................................................ 109 2.4 Inferences on Means and Variances of Normal Distribution: The Parametric Tests............................. 114 2.4.1 The Comparison of Two Means.............................. 114 2.4.2 The Comparison of Two Variances......................... 123 2.4.3 The Comparison of Multiple Means....................... 124 2.5 Inference on Medians and Other Distributions Than Normal: Non-parametric Tests................................... 143 2.5.1 The Comparison of Two-Groups.............................. 143 2.5.2 The Comparison of Several Groups.......................... 150 2.6 Inference on the Relation of Two Quantitative Variables........................................................................ 153 2.6.1 Correlation.................................................................. 154 2.6.2 Regression.................................................................... 162 2.7 Inference on Survival Curves.................................................. 174 2.7.1 Introduction: Assumptions and Definitions............. 174 2.7.2 Kaplan Meier Method................................................ 175 2.7.3 Actuarial Method......................................................... 181 2.7.4 Comparison of Survival Curves................................. 183 2.8 Choosing the Appropriate Bivariate Statistical Test............. 191 2.8.1 Introduction.................................................................. 191 2.8.2 The
Unpaired Statistical Tests................................... 193 2.8.3 The Paired Statistical Tests....................................... 194 2.8.4 The Comparison of Survival Curves........................ 194
Contents xvii 3 2.9 Adjusting Bivariate Analysis:PrognosticStudies................... 2.9.1 Introduction................................................................ 2.9.2 Excluding a Qualitative (Reverse) Interaction .... 2.9.3 Adjusting Two Proportions..................................... 2.9.4 Adjusting Two Means.............................................. 2.9.5 Adjusting Two Quantitative Variables.................... 2.10 Measuring Agreementand TestingReliability....................... 2.10.1 Introduction............................................................... 2.10.2 Plan of the Analysis................................................ 2.10.3 The Qualitative Outcome......................................... 2.10.4 The Quantitative Outcome....................................... References............................................................................................. 195 195 197 200 203 209 213 213 215 218 228 244 Multivariable Analysis....................................................................... 3.1 Introduction............................................................................... 3.2 The ANOVA Family............................................................... 3.2.1 Testing the Main Effects.......................................... 3.2.2 Testing Interaction Effects of Qualitative Variables...................................................... 251 3.2.3 Testing Interaction Effects of Quantitative Variables: Analysis of Covariance (ANCOVA).................................................. 254 3.2.4 Multivariate ANOVA and ANCOVA
(MANOVA and MANCOVA)................... 271 3.2.5 Repeated Measures ANOVA (RMANOVA).......... 3.3 General Outlines of Multivariable Models........................... 3.3.1 Indications................................................................... 3.3.2 Aim of the Model...................................................... 3.3.3 Selection of Predictors............................................... 3.3.4 Model Selection.......................................................... 3.3.5 The Equations and Estimation of Regression Coefficients.................................................. 297 3.3.6 Evaluation of the Model........................................... 3.4 Multiple Regression Analysis................................................. 3.4.1 Introduction: Simple Versus MultipleLinear Regression.................................................................. 3.4.2 The Basic Assumptions............................................. 3.4.3 The Example............................................................... 3.4.4 Designing the Model................................................. 3.4.5 Verification of the Assumptions.............................. 3.4.6 Model Evaluation...................................................... 3.4.7 What Should Be Reported........................................ 3.4.8 The Case of Multiple Outcome Variables.............. 3.5 Binary Logistic Regression Analysis...................................... 3.5.1 Introduction: The Linear Versus the Logistic Regression.................................................................. 3.5.2 The
Basic Assumptions............................................. 3.5.3 The Example.............................................................. 247 247 248 249 277 294 294 294 295 296 298 299 300 301 303 305 306 310 314 315 315 315 322 323
Contents xviii 4 3.5.4 Designing the Model.................................................. 3.5.5 Verification of the Assumptions.............................. 3.5.6 Model Evaluation...................................................... 3.5.7 What Should Be Reported......................................... 3.6 Cox Regression Analysis........................................................ 3.6.1 Introduction: Life Tables Versus Cox Regression Analysis................................................... 3.6.2 The Basic Assumptions.............................................. 3.6.3 The Example............................................................... 3.6.4 Designing the Model.................................................. 3.6.5 Verification of the Assumptions............................... 3.6.6 Model Evaluation....................................................... 3.6.7 What Should Be Reported......................................... References............................................................................................. 324 324 325 328 329 Sample Size Calculation.................................................................. 4.1 Introduction.............................................................................. 4.1.1 Estimation of the Effect Size..................................... 4.1.2 Choosing the Risks of Error..................................... 4.1.3 The Direction of the Study....................................... 4.1.4 Study Specific Factors................................................ 4.1.5 Sample Size
Calculation........................................... 4.2 Comparison of Two Independent Quantitative Variables: Student and Mann Whitney Tests...... 350 4.2.1 Effect Size................................................................... 4.2.2 Sample Size................................................................ 4.3 Association of Two Independent Binary Variables: Chi-Square and Fisher’s Exact Tests.......................... 356 4.3.1 Effect Size................................................................... 4.3.2 Sample Size................................................................. 4.4 Categorical and Ordinal Variables: Chi-Square Tests of Independence and Goodness of Fit......................... 4.4.1 Effect Size................................................................... 4.4.2 Sample Size................................................................ 4.5 Paired Analysis.......................................................................... 4.5.1 Paired Student Test.................................................... 4.5.2 Paired Wilcoxon-Sign-Rank Test.............................. 4.5.3 McNemar’s Test........................................................ 4.6 Comparison of Multiple Means: One-WayANOVA.............. 4.6.1 Effect Size.................................................................... 4.6.2 Sample Size................................................................. 4.7 Simple Correlation: Pearson’s Correlation Coefficient R............................................................................. 4.7.1 Effect
Size................................................................... 4.7.2 Sample Size................................................................ 339 339 340 341 342 343 344 329 330 332 333 333 335 336 337 350 352 356 359 362 363 364 366 366 368 370 372 372 375 377 378 378
xix Contents Simple Linear Regression....................................................... 4.8.1 Effect Size................................................................. 4.8.2 Sample Size............................................................... 4.9 Time to Event.......................................................................... 4.9.1 Effect Size................................................................. 4.9.2 Sample Size............................................................... 4.10 Logistic Regression................................................................. 4.10.1 Effect Size: Log Odds Ratio................................... 4.10.2 Sample Size............................................................... 4.11 Multiple Regression............................................................... 4.11.1 Conditional Fixed Factors Model............................ 4.11.2 Unconditional Random Effect Model..................... 4.12 Repeated Measures.................................................................. 4.12.1 Repeated Measures ANOVA (RMANOVA)........ 4.12.2 Friedman Test........................................................... 4.13 Non-inferiority and Equivalence Studies.............................. 4.13.1 Comparison of 2 Means......................................... 4.13.2 Comparison of Two Proportions............................ 4.13.3 Time to Event Analysis........................................... 4.14 Diagnostic Accuracy............................................................... 4.14.1 Sensitivity and
Specificity....................................... 4.14.2 ROC Analysis........................................................... 4.15 Measuring Agreement............................................................. 4.15.1 Qualitative Outcome................................................ 4.15.2 Quantitative Outcome.............................................. 4.16 Survey Analysis...................................................................... 4.16.1 Introduction............................................................... 4.16.2 Factors Regulating Sample Size Calculation........ 4.16.3 Sample Size Calculation......................................... References............................................................................................. 4.8 5 The Protocol of a Comparative Clinical Study: Statistical Considerations.......................................................... 5.1 Backgroundand Rationale....................................................... 5.2 Objecti ves................................................................................... 5.3 Study Design............................................................................ 5.3.1 The Formulation of the Study.................................. 5.3.2 Number of Study Groups andNumber of Effectuated Comparisons...................................... 5.3.3 The Classic Parallel Groups VersusOther Designs....................................................................... 5.3.4 Design Framework: Superiority, Non-inferiority, Equivalence or Pilot
Study...................................... 5.3.5 Allocation Ratio........................................................... 5.4 Methods..................................................................................... 5.4.1 Study Endpoints........................................................ 5.4.2 Assignment of Interventions.................................... 5.4.3 Blinding (Masking).................................................... 379 379 379 381 381 381 384 385 385 387 387 389 391 391 395 397 398 400 403 405 405 408 410 410 411 413 413 413 414 416 421 421 421 422 422 422 423 423 423 424 424 424 428
Contents XX 5.5 Study Population and Samples............................................... 5.5.1 Study Settings............................................................. 5.5.2 Inclusion Criteria......................................................... 5.5.3 Exclusion Criteria...................................................... 5.5.4 Study Timeline........................................................... 5.5.5 Follow-Up.................................................................... 5.6 Treatments and Interventions................................................. 5.6.1 Studied Treatments and Interventions..................... 5.6.2 Associated Treatments and Interventions................. 5.7 Data Management.................................................................... 5.7.1 Data Collection and Storage..................................... 5.7.2 Data Monitoring and Auditing................................... 5.8 Statistical Methods.................................................................. 5.8.1 Population for the Analysis....................................... 5.8.2 Statistical Hypothesis................................................... 5.8.3 Statistical Analysis....................................................... 5.8.4 Sample Size Determination........................................ 5.9 Study Documentations............................................................ 5.10 Study Ethics.............................................................................. 5.11 Data Sharing and Publication.................................................
5.12 Appendices................................................................................ References.............................................................................................. 6 Introduction to Meta-Analysis........................................................ 6.1 Introduction.............................................................................. 6.1.1 From Narrative to Systematic Review..................... 6.1.2 Why Do We Need Meta-Analysis?.......................... 6.1.3 Types of Meta-Analysis.............................................. 6.2 Stages of Meta-Analysis.......................................................... 6.2.1 Formulation of the Problem....................................... 6.2.2 Data Collection........................................................... 6.2.3 Assessment of Risk of Bias........................................ 6.2.4 Choosing the Model................................................... 6.2.5 Managing the Effect Size Estimates.......................... 6.2.6 Estimation of a Mean Effect Size, Se, 95% CI and P Value................................................. 6.2.7 Assessment of Heterogeneity.................................... 6.2.8 Subgroup Analysis...................................................... 6.2.9 Meta Regression......................................................... 6.2.10 Assessment of Publication Bias and Small-Study Effects........................................................... 503 6.2.11 Sensitivity Analysis..................................................... 6.2.12 Reporting
Meta-Analysis........................................... 6.3 Psychometric Meta-Analysis (Hunter and Schmidt)........... 6.3.1 The Basic Concept.................................................... 6.3.2 The Bare Bones Meta-Analysis................................. 6.3.3 Meta-Analysis Corrected for All Artifacts............... References............................................................................................. 428 428 428 429 430 430 431 431 432 432 432 432 433 433 433 434 435 437 438 438 438 438 441 441 441 442 443 444 445 446 447 447 449 452 479 486 498 511 513 519 519 520 521 523
Contents xxi 7 Pitfalls and Common Errors........................................................... 527 7.1 Sample Size Calculation.......................................................... 527 7.1.1 Empower the Study.................................................... 527 7.1.2 Sculpture the Primary Outcome................................ 528 7.1.3 Reduce Variability byAmeliorating the Study Design....................................................... 535 7.1.4 Prepare the Study to Receive the Selected Tests............................................................. 537 7.1.5 Account for the Effect of Covariates in MultivariableAnalysis............................. 540 7.1.6 Manage the Secondary Outcomes............................ 540 7.2 Data Management..................................................................... 541 7.2.1 Check on Errors and Data Consistency................... 541 7.2.2 Verify Outliers............................................................. 541 7.2.3 Manage Missing Data................................................ 541 7.2.4 Normalizing Data...................................................... 545 7.3 Tools of the Analysis............................................................... 547 7.3.1 The Statistical Software.............................................. 547 7.3.2 The Complementary Online Calculators................. 551 7.4 Data Reporting in a Manuscript............................................. 554 7.4.1 The Introduction........................................................ 554 7.4.2 The Material and
Methods......................................... 555 7.4.3 The Results................................................................. 560 7.4.4 The Discussion.......................................................... 566 7.4.5 The Abstract............................................................... 568 7.4.6 Common Pitfalls, Misinterpretations, andInadequateReporting............................ 569 7.5 The Role oftheStatistician...................................................... 576 7.5.1 Include the Statistician in theResearch Team .... 576 7.5.2 Begin from the Beginning......................................... 577 7.5.3 The Protocol is not a One-Man Show..................... 577 7.5.4 Meeting Mid-Way...................................................... 578 7.5.5 Data Management...................................................... 578 7.5.6 Statistical Analysis...................................................... 579 7.5.7 Publication................................................................... 579 References............................................................................................. 579 List of Equations...................................................................................... 583 Index.......................................................................................................... 609
Ahmed Hassouna Statistics for Clinicians How Much Should a Doctor Know? How much statistics does a clinician, surgeon or nurse need to know? This book provides an essential handbook to help appraise evidence in a scientific paper, to design and interpret the results of research correctly, to guide our students and to review the work of our colleagues. This title is written by a clinician exclusively for fellow clinicians, in their own language and not in statistical or epidemiological terms. When clinicians discuss probability, it is focussed on how it applies to the management of patients in the flesh and how they are managed in a clinical setting. Statistics for Clinicians does not overlook the basis of statistics, but reviews techniques specific to medicine with an emphasis on their application. It ensures that readers have the correct tools to hand, including worked examples, guides and links to online calculators and free software, enabling readers to execute most statistical calculations. This book will therefore be enormously helpful for many working across all fields of medicine at any stage of their career.
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Contents 1 Expressing and Analyzing Variability. 1.1 Introduction. 1.2 Variables: Types, Measurement and Role. 1.2.1 Variable Conversion. 1.3 Summarizing Data. 1.3.1 The Qualitative Variable. 1.3.2 The Quantitative Variable. 1.3.3 Measures of Central Tendency. 1.3.4 Measures of Dispersion. 1.4 The Normal Distribution. 1.4.1 The Standardized Normal Distribution and the Z Score. 1.4.2 The Confidence Interval (CI). 1.4.3 Verifying Normality. 1.4.4 Normalization of Data. 1.5 The P-value. 1.5.1 The Primary Risk of Error (a). 1.6 The Null and Alternative Hypothesis. 1.6.1 Statistical Significance and the Degree of Significance. 1.7 Testing Hypothesis. 1.7.1 A
Simple Parametric Test. 1.7.2 Unilateral Study Design. 1.7.3 Bilateral Study Design. 1.7.4 The Secondary Risk of Error. 1.8 Common Indices of Clinical Outcomes. 1.8.1 The Risk and the Odds. 1.8.2 The Relative Risks and the Odds Ratio. 1.8.3 The Hazard Ratio. 1.8.4 Relative Risk Increase (RRI) and Relative Risk Reduction (RRR). 1.8.5 Absolute Risk Increase (ARI) and Reduction (ARR). 1.8.6 Number Needed to Treat Benefit (NNTB) and Number Needed to Harm (NNTH). 1.8.7 Calculation of the 95% Confidence Interval 51 and Testing Statistical Significance. 1 1 2 2 3 4 7 7 7 10 12 15 25 30 31 31 32 34 34 34 34 36 37 39 39 39 43 49 50 50 XV
Contents xvi Diagnostic Accuracy. 1.9.1 The Discriminative Measures. 1.9.2 The Predictive Values. 1.9.3 The Likelihood Ratios. 1.9.4 Single Indicators of Test Performance. 1.9.5 Choosing the Appropriate Diagnostic Test. 1.9.6 Comparing Two Diagnostic Tests. 1.9.7 The Standards for Reporting Diagnostic Accuracy (STARD). References. 1.9 2 56 57 63 66 71 82 83 85 85 Bivariate Statistical Analysis. 87 2.1 Choosing a Statistical Test. 88 2.1.1 Independence of Data: Paired Versus Unpaired Tests. 89 2.1.2 Data Distribution: Parametric Versus Distribution-Free Tests. 89 2.2 Consulting Statistical Tables. 90 2.2.1 The Test Statistics. 90 2.2.2 The Degrees of Freedom (Df). 91 2.2.3 Consulting IndividualTables. 93 2.3 Inferences on Two Qualitative Variables. 97 2.3.1 The Unpaired
Tests. 97 2.3.2 The Paired Tests. 109 2.4 Inferences on Means and Variances of Normal Distribution: The Parametric Tests. 114 2.4.1 The Comparison of Two Means. 114 2.4.2 The Comparison of Two Variances. 123 2.4.3 The Comparison of Multiple Means. 124 2.5 Inference on Medians and Other Distributions Than Normal: Non-parametric Tests. 143 2.5.1 The Comparison of Two-Groups. 143 2.5.2 The Comparison of Several Groups. 150 2.6 Inference on the Relation of Two Quantitative Variables. 153 2.6.1 Correlation. 154 2.6.2 Regression. 162 2.7 Inference on Survival Curves. 174 2.7.1 Introduction: Assumptions and Definitions. 174 2.7.2 Kaplan Meier Method. 175 2.7.3 Actuarial Method. 181 2.7.4 Comparison of Survival Curves. 183 2.8 Choosing the Appropriate Bivariate Statistical Test. 191 2.8.1 Introduction. 191 2.8.2 The
Unpaired Statistical Tests. 193 2.8.3 The Paired Statistical Tests. 194 2.8.4 The Comparison of Survival Curves. 194
Contents xvii 3 2.9 Adjusting Bivariate Analysis:PrognosticStudies. 2.9.1 Introduction. 2.9.2 Excluding a Qualitative (Reverse) Interaction . 2.9.3 Adjusting Two Proportions. 2.9.4 Adjusting Two Means. 2.9.5 Adjusting Two Quantitative Variables. 2.10 Measuring Agreementand TestingReliability. 2.10.1 Introduction. 2.10.2 Plan of the Analysis. 2.10.3 The Qualitative Outcome. 2.10.4 The Quantitative Outcome. References. 195 195 197 200 203 209 213 213 215 218 228 244 Multivariable Analysis. 3.1 Introduction. 3.2 The ANOVA Family. 3.2.1 Testing the Main Effects. 3.2.2 Testing Interaction Effects of Qualitative Variables. 251 3.2.3 Testing Interaction Effects of Quantitative Variables: Analysis of Covariance (ANCOVA). 254 3.2.4 Multivariate ANOVA and ANCOVA
(MANOVA and MANCOVA). 271 3.2.5 Repeated Measures ANOVA (RMANOVA). 3.3 General Outlines of Multivariable Models. 3.3.1 Indications. 3.3.2 Aim of the Model. 3.3.3 Selection of Predictors. 3.3.4 Model Selection. 3.3.5 The Equations and Estimation of Regression Coefficients. 297 3.3.6 Evaluation of the Model. 3.4 Multiple Regression Analysis. 3.4.1 Introduction: Simple Versus MultipleLinear Regression. 3.4.2 The Basic Assumptions. 3.4.3 The Example. 3.4.4 Designing the Model. 3.4.5 Verification of the Assumptions. 3.4.6 Model Evaluation. 3.4.7 What Should Be Reported. 3.4.8 The Case of Multiple Outcome Variables. 3.5 Binary Logistic Regression Analysis. 3.5.1 Introduction: The Linear Versus the Logistic Regression. 3.5.2 The
Basic Assumptions. 3.5.3 The Example. 247 247 248 249 277 294 294 294 295 296 298 299 300 301 303 305 306 310 314 315 315 315 322 323
Contents xviii 4 3.5.4 Designing the Model. 3.5.5 Verification of the Assumptions. 3.5.6 Model Evaluation. 3.5.7 What Should Be Reported. 3.6 Cox Regression Analysis. 3.6.1 Introduction: Life Tables Versus Cox Regression Analysis. 3.6.2 The Basic Assumptions. 3.6.3 The Example. 3.6.4 Designing the Model. 3.6.5 Verification of the Assumptions. 3.6.6 Model Evaluation. 3.6.7 What Should Be Reported. References. 324 324 325 328 329 Sample Size Calculation. 4.1 Introduction. 4.1.1 Estimation of the Effect Size. 4.1.2 Choosing the Risks of Error. 4.1.3 The Direction of the Study. 4.1.4 Study Specific Factors. 4.1.5 Sample Size
Calculation. 4.2 Comparison of Two Independent Quantitative Variables: Student and Mann Whitney Tests. 350 4.2.1 Effect Size. 4.2.2 Sample Size. 4.3 Association of Two Independent Binary Variables: Chi-Square and Fisher’s Exact Tests. 356 4.3.1 Effect Size. 4.3.2 Sample Size. 4.4 Categorical and Ordinal Variables: Chi-Square Tests of Independence and Goodness of Fit. 4.4.1 Effect Size. 4.4.2 Sample Size. 4.5 Paired Analysis. 4.5.1 Paired Student Test. 4.5.2 Paired Wilcoxon-Sign-Rank Test. 4.5.3 McNemar’s Test. 4.6 Comparison of Multiple Means: One-WayANOVA. 4.6.1 Effect Size. 4.6.2 Sample Size. 4.7 Simple Correlation: Pearson’s Correlation Coefficient R. 4.7.1 Effect
Size. 4.7.2 Sample Size. 339 339 340 341 342 343 344 329 330 332 333 333 335 336 337 350 352 356 359 362 363 364 366 366 368 370 372 372 375 377 378 378
xix Contents Simple Linear Regression. 4.8.1 Effect Size. 4.8.2 Sample Size. 4.9 Time to Event. 4.9.1 Effect Size. 4.9.2 Sample Size. 4.10 Logistic Regression. 4.10.1 Effect Size: Log Odds Ratio. 4.10.2 Sample Size. 4.11 Multiple Regression. 4.11.1 Conditional Fixed Factors Model. 4.11.2 Unconditional Random Effect Model. 4.12 Repeated Measures. 4.12.1 Repeated Measures ANOVA (RMANOVA). 4.12.2 Friedman Test. 4.13 Non-inferiority and Equivalence Studies. 4.13.1 Comparison of 2 Means. 4.13.2 Comparison of Two Proportions. 4.13.3 Time to Event Analysis. 4.14 Diagnostic Accuracy. 4.14.1 Sensitivity and
Specificity. 4.14.2 ROC Analysis. 4.15 Measuring Agreement. 4.15.1 Qualitative Outcome. 4.15.2 Quantitative Outcome. 4.16 Survey Analysis. 4.16.1 Introduction. 4.16.2 Factors Regulating Sample Size Calculation. 4.16.3 Sample Size Calculation. References. 4.8 5 The Protocol of a Comparative Clinical Study: Statistical Considerations. 5.1 Backgroundand Rationale. 5.2 Objecti ves. 5.3 Study Design. 5.3.1 The Formulation of the Study. 5.3.2 Number of Study Groups andNumber of Effectuated Comparisons. 5.3.3 The Classic Parallel Groups VersusOther Designs. 5.3.4 Design Framework: Superiority, Non-inferiority, Equivalence or Pilot
Study. 5.3.5 Allocation Ratio. 5.4 Methods. 5.4.1 Study Endpoints. 5.4.2 Assignment of Interventions. 5.4.3 Blinding (Masking). 379 379 379 381 381 381 384 385 385 387 387 389 391 391 395 397 398 400 403 405 405 408 410 410 411 413 413 413 414 416 421 421 421 422 422 422 423 423 423 424 424 424 428
Contents XX 5.5 Study Population and Samples. 5.5.1 Study Settings. 5.5.2 Inclusion Criteria. 5.5.3 Exclusion Criteria. 5.5.4 Study Timeline. 5.5.5 Follow-Up. 5.6 Treatments and Interventions. 5.6.1 Studied Treatments and Interventions. 5.6.2 Associated Treatments and Interventions. 5.7 Data Management. 5.7.1 Data Collection and Storage. 5.7.2 Data Monitoring and Auditing. 5.8 Statistical Methods. 5.8.1 Population for the Analysis. 5.8.2 Statistical Hypothesis. 5.8.3 Statistical Analysis. 5.8.4 Sample Size Determination. 5.9 Study Documentations. 5.10 Study Ethics. 5.11 Data Sharing and Publication.
5.12 Appendices. References. 6 Introduction to Meta-Analysis. 6.1 Introduction. 6.1.1 From Narrative to Systematic Review. 6.1.2 Why Do We Need Meta-Analysis?. 6.1.3 Types of Meta-Analysis. 6.2 Stages of Meta-Analysis. 6.2.1 Formulation of the Problem. 6.2.2 Data Collection. 6.2.3 Assessment of Risk of Bias. 6.2.4 Choosing the Model. 6.2.5 Managing the Effect Size Estimates. 6.2.6 Estimation of a Mean Effect Size, Se, 95% CI and P Value. 6.2.7 Assessment of Heterogeneity. 6.2.8 Subgroup Analysis. 6.2.9 Meta Regression. 6.2.10 Assessment of Publication Bias and Small-Study Effects. 503 6.2.11 Sensitivity Analysis. 6.2.12 Reporting
Meta-Analysis. 6.3 Psychometric Meta-Analysis (Hunter and Schmidt). 6.3.1 The Basic Concept. 6.3.2 The Bare Bones Meta-Analysis. 6.3.3 Meta-Analysis Corrected for All Artifacts. References. 428 428 428 429 430 430 431 431 432 432 432 432 433 433 433 434 435 437 438 438 438 438 441 441 441 442 443 444 445 446 447 447 449 452 479 486 498 511 513 519 519 520 521 523
Contents xxi 7 Pitfalls and Common Errors. 527 7.1 Sample Size Calculation. 527 7.1.1 Empower the Study. 527 7.1.2 Sculpture the Primary Outcome. 528 7.1.3 Reduce Variability byAmeliorating the Study Design. 535 7.1.4 Prepare the Study to Receive the Selected Tests. 537 7.1.5 Account for the Effect of Covariates in MultivariableAnalysis. 540 7.1.6 Manage the Secondary Outcomes. 540 7.2 Data Management. 541 7.2.1 Check on Errors and Data Consistency. 541 7.2.2 Verify Outliers. 541 7.2.3 Manage Missing Data. 541 7.2.4 Normalizing Data. 545 7.3 Tools of the Analysis. 547 7.3.1 The Statistical Software. 547 7.3.2 The Complementary Online Calculators. 551 7.4 Data Reporting in a Manuscript. 554 7.4.1 The Introduction. 554 7.4.2 The Material and
Methods. 555 7.4.3 The Results. 560 7.4.4 The Discussion. 566 7.4.5 The Abstract. 568 7.4.6 Common Pitfalls, Misinterpretations, andInadequateReporting. 569 7.5 The Role oftheStatistician. 576 7.5.1 Include the Statistician in theResearch Team . 576 7.5.2 Begin from the Beginning. 577 7.5.3 The Protocol is not a One-Man Show. 577 7.5.4 Meeting Mid-Way. 578 7.5.5 Data Management. 578 7.5.6 Statistical Analysis. 579 7.5.7 Publication. 579 References. 579 List of Equations. 583 Index. 609
Ahmed Hassouna Statistics for Clinicians How Much Should a Doctor Know? How much statistics does a clinician, surgeon or nurse need to know? This book provides an essential handbook to help appraise evidence in a scientific paper, to design and interpret the results of research correctly, to guide our students and to review the work of our colleagues. This title is written by a clinician exclusively for fellow clinicians, in their own language and not in statistical or epidemiological terms. When clinicians discuss probability, it is focussed on how it applies to the management of patients in the flesh and how they are managed in a clinical setting. Statistics for Clinicians does not overlook the basis of statistics, but reviews techniques specific to medicine with an emphasis on their application. It ensures that readers have the correct tools to hand, including worked examples, guides and links to online calculators and free software, enabling readers to execute most statistical calculations. This book will therefore be enormously helpful for many working across all fields of medicine at any stage of their career. |
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| spelling | Hassouna, Ahmed 1957- Verfasser (DE-588)1286453895 aut Statistics for clinicians how much should a doctor know? Ahmed Hassouna Cham Springer 2023 xl, 610 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier Medizinische Statistik (DE-588)4127563-9 gnd rswk-swf Medizinische Statistik (DE-588)4127563-9 s DE-604 Erscheint auch als Online-Ausgabe 978-3-031-20758-7 Digitalisierung UB Augsburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034124825&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Augsburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034124825&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Hassouna, Ahmed 1957- Statistics for clinicians how much should a doctor know? Medizinische Statistik (DE-588)4127563-9 gnd |
| subject_GND | (DE-588)4127563-9 |
| title | Statistics for clinicians how much should a doctor know? |
| title_auth | Statistics for clinicians how much should a doctor know? |
| title_exact_search | Statistics for clinicians how much should a doctor know? |
| title_exact_search_txtP | Statistics for clinicians how much should a doctor know? |
| title_full | Statistics for clinicians how much should a doctor know? Ahmed Hassouna |
| title_fullStr | Statistics for clinicians how much should a doctor know? Ahmed Hassouna |
| title_full_unstemmed | Statistics for clinicians how much should a doctor know? Ahmed Hassouna |
| title_short | Statistics for clinicians |
| title_sort | statistics for clinicians how much should a doctor know |
| title_sub | how much should a doctor know? |
| topic | Medizinische Statistik (DE-588)4127563-9 gnd |
| topic_facet | Medizinische Statistik |
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