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    1. Naturvetenskap och teknik
    2. Matematik och naturvetenskap
    3. Biologi
    4. Biovetenskap

    Health Science Statistics using R and R Commander

    AvRobin Beaumont

    Häftad, Engelska, 2015

    Del i serien Scion Publishing

    1 371 kr

    Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

    Beskrivning

    Health Science Statistics using R and R Commander has been written for students, researchers and professionals who need a practical guide to the subject.R is an open source statistical package that is finding favour in a wide variety of statistics applications. Initially R was the preserve of trained statisticians. However, it is increasingly being used with non-specialist audiences, at both postgraduate and senior undergraduate levels.The book focuses on the graphical user interface, R Commander, which helps make R more user-friendly for the uninitiated. However, throughout the book, the R code behind R Commander is provided to allow the reader to program directly if required. The book provides both the practical skills and essential knowledge to enable the reader to perform their own statistical analyses in R and to interpret the results appropriately.The book starts with introductory chapters which demonstrate how to install and run R and R Commander effortlessly. It then builds from introductory statistics chapters (calculating correlations and t tests) through to more complex areas (structural equation modelling, log linear regression etc.). Each chapter begins with a thorough introduction to the statistical technique under discussion. Then, working through real-life data, the reader is shown how to do their own analysis using R Commander, followed by a demonstration of how to do this analysis in R directly. The later chapters also show how to write up findings in the correct format. For specific analyses other free applications are introduced to supplement R (OpenEpi, Gpower and ?nyx). Throughout, the reader is given essential tips and advice to help get to grips with carrying out the analysis and intelligently reflecting on the output.Health Science Statistics using R and R Commander is accompanied by an array of web-based material including:additional online chaptersdiscussion boardR code for each chapter multiple choice questionslinks to other resources including websites, blogs and tutorialsHealth Science Statistics using R and R Commander is a comprehensive introduction to statistics in the health sciences combined with a hands-on practical guide to R (and related free software).

    Produktinformation

    • Utgivningsdatum:2015-01-07
    • Mått:210 x 297 x 29 mm
    • Vikt:1 498 g
    • Format:Häftad
    • Språk:Engelska
    • Serie:Scion Publishing
    • Antal sidor:560
    • Förlag:Scion Publishing Ltd
    • ISBN:9781907904318

    Utforska kategorier

    • Biovetenskap inom Naturvetenskap och teknik
    • Epidemiologi och medicinsk statistik inom Medicin

    Innehållsförteckning

    • 1. How this book works2. Statistics and R – Setting the scene3. R – What is it? Two ways to use it4. Downloading and installing the R software – free!5. Starting R6. R Commander: a graphical front end to R7. Packages: the apps8. A quick tutorial – Analysing data shipped with R9. A quick introduction to the R language: R10. Basic statistical techniques11. Summary statistics12. Graphing Distributions of single variables: histograms and density plots13. Histograms and density plots for subgroups defined by factor levels14. Boxplots15. Percentages for each category/factor level16. Samples and populations17. Comparing a sample mean to a population mean: Single sample t test18. Comparing pre-post test means: Paired samples t test19. Comparing 2 sample means: independent samples t test20. Comparing pre-post test median difference: Wilcoxon Matched Pairs Statistic21. Comparing 2 distributions: Mann-Whitney U Statistic22. Comparing an observed proportion to a population value: The Binomial test23. Several independent proportions compared with the average: Two way tables24. Comparing several independent categories: Contingency tables25. Measuring the degree to which two variable co-vary: Correlation26. Measuring the influence of one variable on another: Regression27. Health Statistics28. Risk and odds ratios29. Number needed to treat/harm (NNT/NNH)30. Sensitivity, Specificity, predictive values and likelihood ratios31. Levels of agreement: Kappa, Krippendorff and the ICC32. Bland-Altman plots33. Meta-analysis: the basics34. Plotting survival over time: K-M (Kaplan-Meier) plots35. Investigating effects upon survival over time: Cox PH regression36. Graphical summaries of data: Aggregation37. Paired nominal data: comparing proportions using McNemar’s test38. Managing your data and R39. Creating datasets and distributions in R Commander and R40. Importing your data into R41. Cutting and Pasting from Excel/Word to the R Data editor42. Saving and exporting your work and data43. R Script files (.R)44. Manipulating variables (columns) in R Commander and R45. Manipulating cases (rows) in R Commander and R46. Expanding tables of counts into flat files47. Installing non-CRANS packages48. Workspaces, objects and history files49. Developing R Code: Rstudio and NppToR50. More ways of analysing your data51. Mosaic and extended association plots52. Multiway tables and Crosstabs53. Resampling: Permutations, Jackknives and Bootstraps54. Repeated measures: Mixed models and Gee55. Sample size requirements56. Confidence intervals for effect sizes: Noncentral distributions57. Publication quality graphics58. More Regression Techniques59. Multiple Linear Regression: Measuring the influence of several variables on a continuous variable60. Logistic regression: a binary outcome61. Poisson (log-linear) Regression62. Conditional Logistic Regression63. Factorial Anova64. Factor Analysis65. Structural Equation Modelling (SEM)66. SummaryAppendicesGlossaryIndex