Clinical Data Analysis on a Pocket Calculator
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Clinical Data Analysis on a Pocket Calculator
Understanding the Scientific Methods of Statistical Reasoning and Hypothesis Testing
Cleophas, Ton J.; Zwinderman, Aeilko H.
Springer International Publishing AG
03/2018
334
Mole
Inglês
9783319800745
15 a 20 dias
551
Descrição não disponível.
Preface.-I Continuous Outcome Data.- Data Spread, Standard Deviations.- Data Summaries:
Histograms, Wide and Narrow Gaussian Curves.- Null-Hypothesis Testing with
Graphs.- Null-Hypothesis Testing with the T-table.- One-Sample Continuous Data (One-Sample
T-Test, One-Sample Wilcoxon.- Paired Continuous Data (Paired T-Test, Two-Sample
Wilcoxon Signed Rank Test).- Unpaired Continuous Data (Unpaired T-Test,
Mann-Whitney).- Linear Regression (Regression Coefficients, Correlation
Coefficients, and their Standard
Errors).- Kendall-Tau Regression
for Ordinal Data.- Paired Continuous Data, Analysis with Help of Correlation
Coefficients.- Power Equations.- Sample Size Calculations.- Confidence
Intervals.- Equivalence Testing instead of Null-Hypothesis Testing.- Noninferiority
Testing instead of Null-Hypothesis Testing.- Superiority Testing instead of
Null-Hypothesis Testing.- Missing Data Imputation.- Bonferroni Adjustments.- Unpaired Analysis of Variance
(ANOVA).- Paired Analysis of Variance (ANOVA).-Variability
Analysis for One or Two Samples.- 22 Variability Analysis for Three or More Samples.-
Confounding.- Propensity Score and Propensity Score Matching for Multiple
Confounders.- Interaction.- Accuracy and Reliability Assessments.- Robust Tests
for Imperfect Data.- Non-linear Modeling on a Pocket Calculator.- Fuzzy
Modeling for Imprecise and Incomplete Data.-
Bhattacharya Modeling for Unmasking Hidden Gaussian Curves.- Item Response
Modeling instead of Classical Linear Analysis of Questionnaires.- Meta-Analysis.- Goodness of Fit Tests for Identifying Nonnormal Data.-
Non-Parametric Tests for Three or More Samples (Friedman and Kruskal-Wallis).- II
Binary Outcome Data.-Data Spread: Standard
Deviation, One Sample Z- Test, One Sample Binomial Test.- Z-Tests.- Phi Tests
for Nominal Data.- 38 Chi-Square Tests.-
Fisher Exact Tests Convenient for Small Samples.- Confounding.- Interaction.- Chi-square
Tests for Large Cross-Tabs.- Logarithmic Transformations, a Great Help to Statistical
Analyses .- Odds Ratios, a Short-Cut for Analyzing
Cross-Tabs.- Log odds, the Basis of Logistic Regression.- Log Likelihood Ratio Tests
for the Best Precision.- Hierarchical Loglinear Models for Higher Order Cross-Tabs.- McNemar Tests for Paired Cross-Tabs.-
McNemar Odds Ratios.- Power Equations.- Sample Size Calculations.- Accuracy
Assessments.- Reliability Assessments.- Unmasking Fudged Data.- Markov Modeling
for Predictions outside the Range of Observations.- Binary Partitioning with CART (Classification
and Regression Tree) Methods.- Meta-Analysis.- Physicians' Daily Life and the
Scientific Method.- Incident Analysis and the Scientific Method.- Cochran Tests
for Large Paired Cross-Tabs.-Index.
Histograms, Wide and Narrow Gaussian Curves.- Null-Hypothesis Testing with
Graphs.- Null-Hypothesis Testing with the T-table.- One-Sample Continuous Data (One-Sample
T-Test, One-Sample Wilcoxon.- Paired Continuous Data (Paired T-Test, Two-Sample
Wilcoxon Signed Rank Test).- Unpaired Continuous Data (Unpaired T-Test,
Mann-Whitney).- Linear Regression (Regression Coefficients, Correlation
Coefficients, and their Standard
Errors).- Kendall-Tau Regression
for Ordinal Data.- Paired Continuous Data, Analysis with Help of Correlation
Coefficients.- Power Equations.- Sample Size Calculations.- Confidence
Intervals.- Equivalence Testing instead of Null-Hypothesis Testing.- Noninferiority
Testing instead of Null-Hypothesis Testing.- Superiority Testing instead of
Null-Hypothesis Testing.- Missing Data Imputation.- Bonferroni Adjustments.- Unpaired Analysis of Variance
(ANOVA).- Paired Analysis of Variance (ANOVA).-Variability
Analysis for One or Two Samples.- 22 Variability Analysis for Three or More Samples.-
Confounding.- Propensity Score and Propensity Score Matching for Multiple
Confounders.- Interaction.- Accuracy and Reliability Assessments.- Robust Tests
for Imperfect Data.- Non-linear Modeling on a Pocket Calculator.- Fuzzy
Modeling for Imprecise and Incomplete Data.-
Bhattacharya Modeling for Unmasking Hidden Gaussian Curves.- Item Response
Modeling instead of Classical Linear Analysis of Questionnaires.- Meta-Analysis.- Goodness of Fit Tests for Identifying Nonnormal Data.-
Non-Parametric Tests for Three or More Samples (Friedman and Kruskal-Wallis).- II
Binary Outcome Data.-Data Spread: Standard
Deviation, One Sample Z- Test, One Sample Binomial Test.- Z-Tests.- Phi Tests
for Nominal Data.- 38 Chi-Square Tests.-
Fisher Exact Tests Convenient for Small Samples.- Confounding.- Interaction.- Chi-square
Tests for Large Cross-Tabs.- Logarithmic Transformations, a Great Help to Statistical
Analyses .- Odds Ratios, a Short-Cut for Analyzing
Cross-Tabs.- Log odds, the Basis of Logistic Regression.- Log Likelihood Ratio Tests
for the Best Precision.- Hierarchical Loglinear Models for Higher Order Cross-Tabs.- McNemar Tests for Paired Cross-Tabs.-
McNemar Odds Ratios.- Power Equations.- Sample Size Calculations.- Accuracy
Assessments.- Reliability Assessments.- Unmasking Fudged Data.- Markov Modeling
for Predictions outside the Range of Observations.- Binary Partitioning with CART (Classification
and Regression Tree) Methods.- Meta-Analysis.- Physicians' Daily Life and the
Scientific Method.- Incident Analysis and the Scientific Method.- Cochran Tests
for Large Paired Cross-Tabs.-Index.
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medicine;health care;statistical analyses;clinical data analysis;statistical software analysis;Entomology
Preface.-I Continuous Outcome Data.- Data Spread, Standard Deviations.- Data Summaries:
Histograms, Wide and Narrow Gaussian Curves.- Null-Hypothesis Testing with
Graphs.- Null-Hypothesis Testing with the T-table.- One-Sample Continuous Data (One-Sample
T-Test, One-Sample Wilcoxon.- Paired Continuous Data (Paired T-Test, Two-Sample
Wilcoxon Signed Rank Test).- Unpaired Continuous Data (Unpaired T-Test,
Mann-Whitney).- Linear Regression (Regression Coefficients, Correlation
Coefficients, and their Standard
Errors).- Kendall-Tau Regression
for Ordinal Data.- Paired Continuous Data, Analysis with Help of Correlation
Coefficients.- Power Equations.- Sample Size Calculations.- Confidence
Intervals.- Equivalence Testing instead of Null-Hypothesis Testing.- Noninferiority
Testing instead of Null-Hypothesis Testing.- Superiority Testing instead of
Null-Hypothesis Testing.- Missing Data Imputation.- Bonferroni Adjustments.- Unpaired Analysis of Variance
(ANOVA).- Paired Analysis of Variance (ANOVA).-Variability
Analysis for One or Two Samples.- 22 Variability Analysis for Three or More Samples.-
Confounding.- Propensity Score and Propensity Score Matching for Multiple
Confounders.- Interaction.- Accuracy and Reliability Assessments.- Robust Tests
for Imperfect Data.- Non-linear Modeling on a Pocket Calculator.- Fuzzy
Modeling for Imprecise and Incomplete Data.-
Bhattacharya Modeling for Unmasking Hidden Gaussian Curves.- Item Response
Modeling instead of Classical Linear Analysis of Questionnaires.- Meta-Analysis.- Goodness of Fit Tests for Identifying Nonnormal Data.-
Non-Parametric Tests for Three or More Samples (Friedman and Kruskal-Wallis).- II
Binary Outcome Data.-Data Spread: Standard
Deviation, One Sample Z- Test, One Sample Binomial Test.- Z-Tests.- Phi Tests
for Nominal Data.- 38 Chi-Square Tests.-
Fisher Exact Tests Convenient for Small Samples.- Confounding.- Interaction.- Chi-square
Tests for Large Cross-Tabs.- Logarithmic Transformations, a Great Help to Statistical
Analyses .- Odds Ratios, a Short-Cut for Analyzing
Cross-Tabs.- Log odds, the Basis of Logistic Regression.- Log Likelihood Ratio Tests
for the Best Precision.- Hierarchical Loglinear Models for Higher Order Cross-Tabs.- McNemar Tests for Paired Cross-Tabs.-
McNemar Odds Ratios.- Power Equations.- Sample Size Calculations.- Accuracy
Assessments.- Reliability Assessments.- Unmasking Fudged Data.- Markov Modeling
for Predictions outside the Range of Observations.- Binary Partitioning with CART (Classification
and Regression Tree) Methods.- Meta-Analysis.- Physicians' Daily Life and the
Scientific Method.- Incident Analysis and the Scientific Method.- Cochran Tests
for Large Paired Cross-Tabs.-Index.
Histograms, Wide and Narrow Gaussian Curves.- Null-Hypothesis Testing with
Graphs.- Null-Hypothesis Testing with the T-table.- One-Sample Continuous Data (One-Sample
T-Test, One-Sample Wilcoxon.- Paired Continuous Data (Paired T-Test, Two-Sample
Wilcoxon Signed Rank Test).- Unpaired Continuous Data (Unpaired T-Test,
Mann-Whitney).- Linear Regression (Regression Coefficients, Correlation
Coefficients, and their Standard
Errors).- Kendall-Tau Regression
for Ordinal Data.- Paired Continuous Data, Analysis with Help of Correlation
Coefficients.- Power Equations.- Sample Size Calculations.- Confidence
Intervals.- Equivalence Testing instead of Null-Hypothesis Testing.- Noninferiority
Testing instead of Null-Hypothesis Testing.- Superiority Testing instead of
Null-Hypothesis Testing.- Missing Data Imputation.- Bonferroni Adjustments.- Unpaired Analysis of Variance
(ANOVA).- Paired Analysis of Variance (ANOVA).-Variability
Analysis for One or Two Samples.- 22 Variability Analysis for Three or More Samples.-
Confounding.- Propensity Score and Propensity Score Matching for Multiple
Confounders.- Interaction.- Accuracy and Reliability Assessments.- Robust Tests
for Imperfect Data.- Non-linear Modeling on a Pocket Calculator.- Fuzzy
Modeling for Imprecise and Incomplete Data.-
Bhattacharya Modeling for Unmasking Hidden Gaussian Curves.- Item Response
Modeling instead of Classical Linear Analysis of Questionnaires.- Meta-Analysis.- Goodness of Fit Tests for Identifying Nonnormal Data.-
Non-Parametric Tests for Three or More Samples (Friedman and Kruskal-Wallis).- II
Binary Outcome Data.-Data Spread: Standard
Deviation, One Sample Z- Test, One Sample Binomial Test.- Z-Tests.- Phi Tests
for Nominal Data.- 38 Chi-Square Tests.-
Fisher Exact Tests Convenient for Small Samples.- Confounding.- Interaction.- Chi-square
Tests for Large Cross-Tabs.- Logarithmic Transformations, a Great Help to Statistical
Analyses .- Odds Ratios, a Short-Cut for Analyzing
Cross-Tabs.- Log odds, the Basis of Logistic Regression.- Log Likelihood Ratio Tests
for the Best Precision.- Hierarchical Loglinear Models for Higher Order Cross-Tabs.- McNemar Tests for Paired Cross-Tabs.-
McNemar Odds Ratios.- Power Equations.- Sample Size Calculations.- Accuracy
Assessments.- Reliability Assessments.- Unmasking Fudged Data.- Markov Modeling
for Predictions outside the Range of Observations.- Binary Partitioning with CART (Classification
and Regression Tree) Methods.- Meta-Analysis.- Physicians' Daily Life and the
Scientific Method.- Incident Analysis and the Scientific Method.- Cochran Tests
for Large Paired Cross-Tabs.-Index.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
