E-Book, Englisch, 334 Seiten, eBook
Cleophas / Zwinderman Clinical Data Analysis on a Pocket Calculator
2. Auflage 2016
ISBN: 978-3-319-27104-0
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
Understanding the Scientific Methods of Statistical Reasoning and Hypothesis Testing
E-Book, Englisch, 334 Seiten, eBook
Reihe: Biomedical and Life Sciences (R0)
ISBN: 978-3-319-27104-0
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
In medical and health care the scientific method is little used, and statistical software programs are experienced as black box programs producing lots of p-values, but little answers to scientific questions. The pocket calculator analyses appears to be, particularly, appreciated, because they enable medical and health professionals and students for the first time to understand the scientific methods of statistical reasoning and hypothesis testing. So much so, that it can start something like a new dimension in their professional world. In addition, a number of statistical methods like power calculations and required sample size calculations can be performed more easily on a pocket calculator, than using a software program. Also, there are some specific advantages of the pocket calculator method. You better understand what you are doing. The pocket calculator works faster, because far less steps have to be taken, averages can be used. The current nonmathematical book is complementary to the nonmathematical "SPSS for Starters and 2nd Levelers" (Springer Heidelberg Germany 2015, from the same authors), and can very well be used as its daily companion.
Zielgruppe
Graduate
Autoren/Hrsg.
Weitere Infos & Material
Preface
I Continuous Outcome Data
1 Data Spread, Standard Deviations
2 Data Summaries: Histograms, Wide and Narrow Gaussian Curves
3 Null-Hypothesis Testing with Graphs
4 Null-Hypothesis Testing with the T-table
5 One-Sample Continuous Data (One-Sample T-Test, One-Sample Wilcoxon
6 Paired Continuous Data (Paired T-Test, Two-Sample Wilcoxon Signed Rank Test)
7 Unpaired Continuous Data (Unpaired T-Test, Mann-Whitney)8 Linear Regression (Regression Coefficients, Correlation Coefficients, and their Standard Errors)
9 Kendall-Tau Regression for Ordinal Data
10 Paired Continuous Data, Analysis with Help of Correlation Coefficients
11 Power Equations
12 Sample Size Calculations
13 Confidence Intervals14 Equivalence Testing instead of Null-Hypothesis Testing
15 Noninferiority Testing instead of Null-Hypothesis Testing
16 Superiority Testing instead of Null-Hypothesis Testing
17 Missing Data Imputation
18 Bonferroni Adjustments
19 Unpaired Analysis of Variance (ANOVA)20 Paired Analysis of Variance (ANOVA)
21 Variability Analysis for One or Two Samples
22 Variability Analysis for Three or More Samples
23 Confounding
24 Propensity Score and Propensity Score Matching for Multiple Confounders
25 Interaction
26 Accuracy and Reliability Assessments27 Robust Tests for Imperfect Data
28 Non-linear Modeling on a Pocket Calculator
29 Fuzzy Modeling for Imprecise and Incomplete Data
30 Bhattacharya Modeling for Unmasking Hidden Gaussian Curves
31 Item Response Modeling instead of Classical Linear Analysis of Questionnaires
32 Meta-Analysis 133 Goodness of Fit Tests for Identifying Nonnormal Data
34 Non-Parametric Tests for Three or More Samples (Friedman and Kruskal-Wallis)
II Binary Outcome Data
35 Data Spread: Standard Deviation, One Sample Z- Test, One Sample BinomialTest
36 Z-Tests
37 Phi Tests for Nominal Data
38 Chi-Square Tests
39 Fisher Exact Tests Convenient for Small Samples
40 Confounding
41 Interaction42 Chi-square Tests for Large Cross-Tabs
43 Logarithmic Transformations, a Great Help to Statistical Analyses
44 Odds Ratios, a Short-Cut for Analyzing Cross-Tabs
45 Logodds, the Basis of Logistic Regression
46 Log Likelihood Ratio Tests for the Best Precision
47 Hierarchical Loglinear Models for Higher Order Cross-Tabs48 McNemar Tests for Paired Cross-Tabs
49 McNemar Odds Ratios
50 Power Equations
51 Sample Size Calculations
52 Accuracy Assessments
53 Reliability Assessments54 Unmasking Fudged Data
55 Markov Modeling for Predictions outside the Range of Observations
56 Binary Partitioning with CART (Classification and Regression Tree) Methods
57 Meta-Analysis
58 Physicians' Daily Life and the Scientific Method
59 Incident Analysis and the Scientific Method60 Cochran Tests for Large Paired Cross-Tabs
Index




