Clinical Data Analysis on a Pocket Calculator : Understanding the Scientific Methods of Statistical Reasoning and Hypothesis Testing /
| Autores principales: | , |
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| Autor Corporativo: | |
| Formato: | eBook |
| Lenguaje: | English |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2016.
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| Edición: | 2nd ed. 2016. |
| Materias: |
Tabla de Contenidos:
- 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. .