Includes bibliographical references and index.

Introductin: the role of statistics in research and clinical practice -- Properties of variables: levels of measurement -- Descriptive univariate statistics -- Probabilities -- Logic of statistical inference: the sampling distribution and significance tests -- Standard errors, confidence intervals and the power of statistical tests -- Research designs and statistical analysis -- T-test -- Oneway analysis of variance -- Linear regression and Pearson's r correlation -- Factorial analysis of variance and analysis of covariance -- Multiple linear regression -- Repeated measures analysis of variance -- Introduction to mixed-effects regression models -- Non-parametric/ordinal statistics -- Frequency cross-tabulations: 2x2 tables -- Logistic regression with one independent variable -- Logistic regression models with multiple predictors -- Incidence rates, life tables and survival function -- Comparing survival functions in different groups and hazard regression -- Reliability coefficients and medical test evaluation -- Factor analysis -- Data management and privacy concerns.

"This comprehensive, graduate-level text for advanced practice nurses and other health care professionals provides state-of-the-art tools that facilitate the reading and interpretation of articles in clinical journals that use increasingly complex statistical techniques. It goes beyond the usual offerings of such texts to address clinically relevant topics in bio-statistics such as survival analysis and evaluation of screening tests. The text emphasizes the importance of understanding the underlying logic of statistical texts and models in order to correctly interpret them and effectively translate them into practice. It will also help readers to choose appropriate statistical methods for conducting their own translational research. With a focus on disseminating information in easily understandable language, the text addresses basic statistical reasoning and four different classes of statistical models. It provides refreshers on the algebraic underpinnings of statistics in the appendices and more complex algebraic derivations in highlighted boxes throughout the text. This includes how to manipulate the exponential expressions and logarithms necessary for logistic and hazard regression models. The book also features clear explanations of more sophisticated statistical models, inference, and analyses. Chapters present examples from current research and multiple exercises designed to reinforce learning. These include both hand calculations and data analysis using SPSS or STATA software. Additionally, data sets for practice are available from the Springer Publishing website with instructions for producing output shown in the text in SPSS, STATA, SAS, and Microsoft Excel formats. A chapter on data management practices and ethical issues of privacy maintenance is also included"--Provided by publisher.

Print version record.