Clinical Biostatistics and Epidemiology Made Ridiculously Simple

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ISBN: 9781935660026 | 1935660020
Cover: Paperback
Copyright: 3/1/2011

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Summary

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The most important points in clinical biostatistics, presented intuitively with clinical examples and a clear approach to interpreting research reports. Book jacket.

Preface	p. viii
Introduction	p. 1
Terminology	p. 2
Population, Sample, and Element	p. 2
Descriptive vs. Inferential Statistics	p. 2
Parameter vs. Statistic	p. 2
Sampling Error vs. Selection Bias	p. 3
Imprecision vs. Bias (Inaccuracy)	p. 3
Validity vs. Reliability	p. 4
Independent vs. Dependent Variables	p. 4
Normal (Gaussian), Skewed, and Kurtotic curves	p. 5
Multiplication and Addition Rules of Probability	p. 7
Statistical Significance vs. Clinical Significance	p. 8
Statistical Abnormality vs. Clinical Abnormality	p. 8
Mean, Median, and Mode	p. 9
Mean	p. 9
Median	p. 9
Mode	p. 9
What's Wrong Here? *#!!	p. 11
Range, Variance, and Standard Deviation	p. 13
Range	p. 13
Variance	p. 14
Standard Deviation	p. 14
Coefficient of Variation	p. 15
Kinds of Data	p. 17
Nominal Data	p. 17
Ordinal Data	p. 17
Interval Data	p. 17
Ratio Data	p. 18
Research Design	p. 19
Kinds of Studies	p. 20
Randomized Control Studies	p. 20
Matching Studies	p. 20
Stratified Randomization Studies	p. 21
Blind Studies	p. 21
Prospective (Cohort; Longitudinal) Studies	p. 21
Retrospective (Case-control) Studies	p. 23
Cross-sectional (Prevalence) Studies	p. 24
Experimental vs. Observational Studies	p. 24
Case Series and Case Reports	p. 25
Meta-analysis	p. 25
Crossover, Between-subjects, and Within-subjects Studies	p. 26
Therapeutic Trials	p. 26
Kinds of Graphs	p. 27
Bar Graphs (Bar Charts)	p. 27
Tables	p. 28
Histograms	p. 28
Line Graphs	p. 29
Cumulative Frequency Curves	p. 30
Box-and-Whiskers Plots	p. 31
Stem-and-Leaf Plots	p. 32
Scattergrams	p. 33
Survival Curves	p. 33
Hypothesis Testing	p. 36
The Null and Alternative Hypotheses	p. 36
Rejecting the Null Hypothesis	p. 37
Statistical Tests	p. 39
Parametric vs. Nonparametric Tests	p. 39
Descriptive Statistics	p. 40
The Z-score	p. 40
Inferential Statistics	p. 43
Confidence Intervals vs. Hypothesis Testing and P-values	p. 43
Standard Error of the Mean (SEM)	p. 46
The Central Limit Theorem	p. 46
Standard Error of the Mean	p. 47
The t-Test	p. 49
The Meaning of the t-Test	p. 49
Comparing Two Samples	p. 49
One-Tailed Vs. Two-Tailed Studies	p. 52
The Two-Tailed Test	p. 52
The One-Tailed Test	p. 53
P-Ing (PEE-ING) All Over the Place	p. 56
Type I and Type II Errors	p. 58
Type I and Type II Errors	p. 58
Power	p. 59
Effect Size	p. 60
Bayesian Thinking	p. 61
Calculation of Sample Size	p. 62
ANOVA (Analysis of Variance)	p. 64
ANOVA and F-ratio	p. 64
MANOVA and ANCOVA	p. 66
Correlation and Regression	p. 68
Correlation Techniques	p. 68
Correlation Does Not Mean Causation	p. 70
Criteria of Causality	p. 71
Regression	p. 72
Kinds of Regression Analysis	p. 73
Regression to the Mean	p. 74
Nonparametric Tests	p. 75
Chi-Square (X²) Goodness-of-Fit Test	p. 75
Nonparametric Tests That Use Ranking	p. 78
Nonparametric Tests That Do Not Use Ranking	p. 79
Epidemiological Tests	p. 80
Incidence vs. Prevalence	p. 80
Mortality, Morbidity, and Case Fatality	p. 81
Absolute Risk vs. Relative Risk (RR)	p. 81
Odds and Odds Ratio (Relative Odds)	p. 82
Absolute Risk Reduction (Attributable Risk) vs. Relative Risk Reduction	p. 83
Number Needed to Treat (NNT)	p. 84
Number Needed to Harm (NNH)	p. 84
Sensitivity vs. Specificity	p. 85
Positive and Negative Predictive Values	p. 87
Are the Research Conclusions Correct?	p. 89
What's Wrong Here?	p. 90
Who Says So?	p. 90
How Does the Researcher Know?	p. 90
What's Missing?	p. 91
Did Someone Change the Subject?	p. 94
Does It Make Sense?	p. 95
The Z table	p. 96
The t table	p. 97
The Chi-Square Table	p. 98
References	p. 99
Index	p. 101
Table of Contents provided by Ingram. All Rights Reserved.

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Clinical Biostatistics and Epidemiology Made Ridiculously Simple

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Table of Contents

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Clinical Biostatistics and Epidemiology Made Ridiculously Simple

Summary

Table of Contents

Supplemental Materials

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