Biostatistics Decoded

ISBN-10: 1119953375

ISBN-13: 9781119953371

Edition: 2013

List price: $98.95
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Description: Biostatistics Decoded presents statistical theory and biostatistical methods and applications. This book looks at sampling methods, study design and statistical methods and relates statistical methods with the corresponding study designs. Biostatistics is presented with a strictly non–mathematical approach, emphasizing statistical theory and methods rather than mathematical proofs and formalisms. The topics featured in this book cover most needs of clinical researchers, both regarding study designs and statistical methods.

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Book details

List price: $98.95
Copyright year: 2013
Publisher: John Wiley & Sons, Limited
Publication date: 8/30/2013
Binding: Paperback
Pages: 346
Size: 6.02" wide x 8.98" long x 0.69" tall
Weight: 0.990
Language: English

The object of biostatisties
Defining the population
Study design
Inferences from samples
Basic concepts
Data reduction
Scales of measurement
Tabulations of data
Central tendency measures
Measures of dispersion
Compressing data
The standard deviation
The n - 1 divisor
Properties of means and variances
Common frequency distributions
The normal distribution
The central limit theorem
Properties of the normal distribution
Statistical tables
Statistical inference
Sampling distributions
The normal distribution of sample means
The standard error of the mean
The value of the standard error
Inferences from means
Confidence intervals
The case of small samples
Student's t distribution
Statistical tables of the t distribution
Estimation with binary variables
The binomial distribution
Inferences from proportions
Statistical tables of the binomial distribution
Sample size requirements
Descriptive studies
Classification of descriptive studies
Probability sampling
Simple random sampling
Replacement in sampling
Stratified sampling
Multistage sampling
Prevalence studies
Incidence studies
The person-years method
Non-probability sampling in descriptive studies
Analytical studies
Design of analytical studies
Non-probability sampling in analytical studies
The investigation of associations
Comparison of two means
Comparison of two means from small samples
Comparison of two proportions
Relative risks and odds ratios
Attributable risk
Logits and log odds ratios
Statistical tests
The null hypothesis
The z-test
The p-value
Student's t-test
The binomial test
The chi-square test
Degrees of freedom
The table of the chi-square distribution
Analysis of variance
Statistical tables of the F distribution
Issues with statistical tests
One-sided tests
Power of a statistical test
Sample size estimation
Multiple comparisons
Scale transformation
Non-parametric tests
Longitudinal studies
Repeated measurements
The paired Student's t-test
McNemar's test
Analysis of events
The actuarial method
The Kaplan-Meier method
The logrank test
The adjusted logrank test
The Poisson distribution
The incidence rate ratio
Statistical modeling
Linear regression
The least squares method
Linear regression estimates
Regression and correlation
The F-test in linear regression
Interpretation of regression analysis results
Multiple regression
Regression diagnostics
Selection of predictor variables
Regression, t-test, and anova
Nonlinear regression
Logistic regression
The method of maximum likelihood
Estimation of the logistic regression model
The likelihood ratio test
Interpreting the results of logistic regression
Regression coefficients and odds ratios
Applications of logistic regression
The ROC curve
Model validation
The Cox proportional hazards model
Assumptions of the Cox model
Interpretation of Cox regression
Construction of clinical questionnaires
Factor analysis
Interpretation of factor analysis
Factor rotation
Factor scores
Experimental studies
The purpose of experimental studies
The clinical trial population
The efficacy criteria
Non-comparative clinical trials
Controlled clinical trials
Classical designs
The control group
The size of a clinical trial
Non-inferiority clinical trials
Adaptive clinical trials
Group sequential plans
The alpha spending function
The clinical trial protocol
The data record
The analysis of experimental studies
General analysis plan
Data preparation
Study populations
Primary efficacy analysis
Analysis of multiple endpoints
Secondary analyses
Safety analysis
Meta-analysis of clinical trials
Purpose of meta-analysis
Measures of treatment effect
The inverse variance method
The random effects model
Publication bias
Presentation of results
Further reading
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