Interpreting Statistical Findings: A Guide for Health Professionals and Students

Häftad, Engelska, 2010

469 kr

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"This book makes the task of interpreting statistical findings much more approachable and less daunting for those with little, or no, previous experience, and will provide a valuable reference for the more experienced researcher. I would recommend it to any student undertaking a Nursing Research module."
Conor Hamilton, Student Nurse, Queen’s University Belfast, UK

Need help interpreting other people's health research?

This book offers guidance for students undertaking a critical review of quantitative research papers and will also help health professionals to understand and interpret statistical results within health-related research papers.

The book requires little knowledge of statistics, includes worked examples and is broken into the following sections:

A worked example of a published RCT and a health survey
Explanations of basic statistical concepts
Explanations of common statistical tests
A quick guide to statistical terms and concepts

Walker and Almond have helpfully cross-referenced throughout, so those requiring in-depth explanations or additional worked examples can locate these easily.

Interpreting Statistical Research Findings is key reading for nursing and health care students and will help make this area of research much easier to tackle!

Produktinformation

Utgivningsdatum2010-07-16
Mått152 x 229 x 11 mm
Vikt355 g
FormatHäftad
SpråkEngelska
Antal sidor232
FörlagMcGraw-Hill Education
ISBN9780335235971

Tillhör följande kategorier

Sociologi inom Samhälle och politik
Epidemiologi och medicinsk statistik inom Medicin

Jan Walker worked as a health visitor for eight years before taking a degree in psychology and then a PhD which focused pain in later life. Working as a university lecturer and reader, she taught psychology on a wide range of courses for nurses, allied health, medical and social care professionals, from introductory to masters level. She has held honorary contracts with several pain clinics, helping individuals to identify goals and resources for self management. She has conducted, supervised and published research on the lived experience of chronic pain and other chronic conditions. Jan is currently a Visiting Senior Research Fellow at the University of Southampton where she works closely with the Complementary Medicine Research Unit.

Part 1 Worked ExamplesThe randomised controlled trialThe Health surveyPart 2 Interpreting statistical conceptsMeasuring variables: continuous, ordinal and categorical dataDescribing continuous data: The normal distributionDescribing nonparametric dataMeasuring concepts: Validity and reliabilitySampling data: Probability and non-probability samplesSample size: criteria for judging adequacyTesting hypotheses: what does p actually mean?Part 3 Statistical testsIntroduction to inferential statisticsComparing two independent (unrelated) groups: independent (unrelated) t test, Mann-Whitney U test, contingency analysis- Fisher's exact test and Chi-square testComparing three or more independent (unrelated) groups: One-way ANOVA, Kruskal Wallis test and Chi-square testComparing two sets of related data: Matched pairs or single-sample repeated measures- related (paired) t test, Wilcoxon signed rank test, sign test and McNemar's testComplex group comparisons: ANOVA / ANCOVA, Friedman two-way ANOVA by ranks and Cochrane Q testSimple tests of association: Correlation and linear regressioncomplex associations: Multiple and logistic regressionPart 4 Quick reference guideI Framework for statistical reviewII Glossary of termsIII Guide to statistical symbolsIV Overview of common statistical testsV Guide to the assumptions that underpin statistical testsVI Summary of statistical test selection and resultsVII Extracts from statistical tables