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.
Key Features:
Covers bio-statistics especially relevant to nursing research such as survival analysis and evaluation of screening tests
Includes research examples from current literature in highlighted boxes
Presents text boxes with algebraic derivations useful to interpreting statistical methods
Provides digital examples for SPSS and STATA with instructions on how to produce output included in text
Offers end-of-chapter exercises involving hand calculations and data analysis using SPSS, STATA, and other software formats
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.
Key Features:
Covers bio-statistics especially relevant to nursing research such as survival analysis and evaluation of screening tests
Includes research examples from current literature in highlighted boxes
Presents text boxes with algebraic derivations useful to interpreting statistical methods
Provides digital examples for SPSS and STATA with instructions on how to produce output included in text
Offers end-of-chapter exercises involving hand calculations and data analysis using SPSS, STATA, and other software formats
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