Epidemiology with R / (Record no. 44142)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 08137cam a22004215i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | CUTN |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250402151316.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 200720s2021 enka b 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 0198841337 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780198841333 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780198841326 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 0198841329 |
| 041 ## - LANGUAGE CODE | |
| Language | English |
| 042 ## - AUTHENTICATION CODE | |
| Authentication code | lccopycat |
| 060 #4 - NATIONAL LIBRARY OF MEDICINE CALL NUMBER | |
| Classification number | WA 950 |
| Item number | .C321e 2021 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 614.407 |
| Edition number | 23 |
| Item number | CAR |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Carstensen, Bendix, |
| 245 10 - TITLE STATEMENT | |
| Title | Epidemiology with R / |
| Statement of responsibility, etc | Bendix Carstensen. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | First edition. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc | UK : |
| Name of publisher, distributor, etc | OUP Oxford, |
| Date of publication, distribution, etc | 2021. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xiv, 231 pages : |
| Other physical details | illustrations ; |
| Dimensions | 25 cm |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Title | Epidemiology with R<br/>Copyright<br/>Contents<br/>Preface<br/>What this book is not<br/>Acknowledgements<br/>List of Figures<br/>Introduction<br/>What you should do<br/>Code chunks<br/>Graphs in this book<br/>Practicing R<br/>Chapter 1: Using R<br/>1.1 Installing and using R<br/>1.2 Documenting your code and results<br/>1.2.1 R markdown<br/>1.2.2 Sweave / knitr<br/>1.2.3 Coding style in R<br/>1.2.4 R lingo<br/>1.3 Simple usage of R<br/>1.3.1 Using R as a calculator<br/>1.3.2 A functional language<br/>Probability functions<br/>Objects and functions<br/>What makes R different: functions<br/>1.3.3 Sequences<br/>1.3.4 The births data<br/>1.3.5 Referencing parts of a data frame<br/>1.3.6 Summaries<br/>1.3.7 Generating new variables<br/>1.3.8 Logical variables<br/>1.3.9 Turning a variable into a factor<br/>Manipulating factor levels<br/>Grouping values of a quantitative variable<br/>1.3.10 Tables<br/>Tables of means and other things<br/>1.3.11 Reading data<br/>1.3.12 Saving data<br/>Saving the work space<br/>Saving R objects in a file<br/>1.3.13 The search path<br/>Attaching a data frame<br/>Using with<br/>1.4 Graphics<br/>1.4.1 ggplot2<br/>1.4.2 Base graphics<br/>1.4.3 Simple base graphs<br/>Plot on the screen<br/>Colours<br/>Adding to a plot<br/>Using indexing for plot elements<br/>Interacting with a plot<br/>Saving graphs for use in other documents<br/>Same graph on multiple devices<br/>The par() command<br/>1.5 Frequency data<br/>1.5.1 Graphical overview<br/>1.5.2 Ad hoc analyses of admissions<br/>1.6 Tables and arrays for results<br/>1.7 Dates in R<br/>1.8 Numerical accuracy<br/>1.8.1 Accuracy of matching variables<br/>1.9 tidyverse and data.table<br/>Chapter 2: Measures of disease occurrence<br/>2.1 Prevalence<br/>2.2 Mortality rate<br/>2.3 Incidence rate<br/>2.4 Standardized mortality ratio<br/>2.5 Survival<br/>2.5.1 Cumulative risk<br/>2.5.2 Competing risks<br/>2.5.3 Sojourn time<br/>Chapter 3: Prevalence data—models, likelihood, and binomial regression<br/>3.1 Likelihood<br/>3.1.1 A single probability<br/>3.1.2 Simple confidence interval<br/>3.1.3 Confidence intervals in general<br/>3.1.4 The normal distribution<br/>3.1.5 Simple confidence intervals from models<br/>3.1.6 Tests and p-values<br/>3.2 Prevalence by age<br/>3.3 Comparing different models for the same data<br/>3.3.1 Likelihood-ratio test<br/>3.3.2 Deviance<br/>3.3.3 Deviance and goodness of fit<br/>3.3.4 AIC and BIC<br/>Chapter 4: Regression models<br/>4.1 Types of models<br/>4.2 Normal linear regression model<br/>4.3 Simple linear regression<br/>4.4 Multiple regression<br/>4.4.1 Estimation in the normal linear regression model<br/>4.4.2 R-squared<br/>4.4.3 Multiple regression<br/>4.4.4 Standardized variables<br/>4.4.5 Predictions from the normal regression model<br/>4.5 Model formulae in R<br/>4.6 Regression models and generalized linear models<br/>4.6.1 Categorical effects<br/>4.6.2 Linear and categorical effects<br/>4.6.3 ANOVA–ANCOVA<br/>4.6.4 Categorical-linear interaction<br/>Special interaction?<br/>4.6.5 Categorical by categorical interaction<br/>4.7 Collinearity and aliasing<br/>4.8 Logarithmic transformations<br/>4.8.1 Logarithms<br/>4.8.2 Log transform of the response variable<br/>4.8.3 Coefficient of variation<br/>4.8.4 Log transform of an explanatory variable<br/>4.8.5 Log transform of both the response and explanatory variables<br/>Chapter 5: Analysis of follow-up data<br/>5.1 Basic data structure<br/>5.2 Probability model<br/>5.2.1 Data<br/>5.2.2 Likelihood for a rate<br/>5.2.3 Estimates of rates and rate ratios<br/>5.3 Representation of follow-up data<br/>5.3.1 Lexis object for follow-up data<br/>Scaling of Lexis diagrams<br/>5.4 Splitting the follow-up time along a time-scale<br/>5.5 Smooth age-effects for rates<br/>5.5.1 Disaggregated data<br/>5.5.2 Including sex in the model<br/>5.6 SMR<br/>5.6.1 Modelling the SMR<br/>5.7 Time-dependent variables<br/>5.7.1 Cutting time at a specific date<br/>The precursor states<br/>5.7.2 Modelling time-dependent variables<br/>Survival?<br/>5.7.3 Clinical measurements in cohort studies<br/>Analysis using clinical measurements<br/>Chapter 6: Parametrization and prediction of rates<br/>6.1 Predictions and contrasts<br/>6.2 Prediction of a single rate<br/>6.3 Categorical variables<br/>6.3.1 Groups and rate ratios<br/>Comparing all groups<br/>6.4 Modelling the effect of quantitative variables<br/>6.4.1 Categorizing quantitative variables: don’t<br/>6.4.2 Linear effect<br/>Predicting the rates<br/>6.4.3 Polynomial effects<br/>6.4.4 Other types of non-linear effects<br/>Natural splines<br/>Penalized splines<br/>6.5 Two quantitative predictors<br/>6.5.1 Age and period<br/>6.5.2 Age and cohort<br/>6.5.3 Contours of joint effects<br/>Image plot / heatmap<br/>6.6 Quantitative interactions<br/>6.6.1 Age–period interaction<br/>Age-specific rates at different dates (periods)<br/>Period-specific rates at different ages<br/>6.6.2 Age and cohort interaction<br/>6.6.3 Parametric interaction models<br/>6.6.4 Varying coefficients models for interaction<br/>6.6.5 Summary of quantitative interactions<br/>Chapter 7: Case-control and case-cohort studies<br/>7.1 Follow-up and case-control studies<br/>7.1.1 Probabilities and odds in case-control studies<br/>7.1.2 The sampling fractions<br/>7.1.3 A simple example<br/>7.2 Statistical model for the odds ratio<br/>7.2.1 Analysis by logistic regression<br/>7.3 Odds ratio and rate ratio<br/>7.3.1 Incidence density sampling<br/>7.4 Confounding and stratified sampling<br/>7.4.1 Stratified sampling<br/>7.5 Individually matched studies<br/>7.5.1 An example<br/>7.5.2 When conditional analysis is not needed<br/>7.6 Nested case-control studies<br/>7.6.1 Register-based case-control studies<br/>7.7 Case-cohort studies<br/>Chapter 8: Survival analysis<br/>8.1 Introduction<br/>8.2 Life table estimator of survival function<br/>8.3 Kaplan--Meier estimator of survival<br/>8.3.1 Survival in two groups<br/>8.4 The Cox model<br/>8.4.1 Mean survival or survival at mean?<br/>8.5 The time-scale<br/>8.6 Relation between Cox and Poisson models<br/>8.6.1 Simple parametric mortality functions<br/>Baseline mortality rate<br/>Survival curves<br/>8.6.2 Proportional hazards?<br/>8.6.3 The Cox model as a Poisson model<br/>8.7 Time-dependent covariates<br/>8.8 Competing risks<br/>8.9 Modelling cause specific rates<br/>8.9.1 Limitations<br/>8.10 The Fine--Gray approach to competing risks<br/>8.11 Time-dependent variables and competing risks<br/>Chapter 9: Do not group quantitative variables<br/>9.1 Problems Caused by Categorizing Continuous Variables<br/>References<br/>Index<br/> |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Epidemiology with R<br/>This practical guide is designed for students and researchers with an existing knowledge of R who wish to learn how to apply it in an epidemiological context and exploit its versatility. It also serves as a broader introduction to the quantitative aspects of modern practical epidemiology. The standard tools used in epidemiology are described and the practical use of R for these is clearly explained and laid out. R code examples, many with output, are embedded throughout the text. The entire code is also available on the companion website so that readers can reproduce all the results and graphs featured in the book. Epidemiology with R is an advanced textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners in the fields of human and non-human epidemiology, public health, veterinary science, and biostatistics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Epidemiology |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | R (Computer program language) |
| 650 #2 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Epidemiology |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Epidemiology |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | R (Computer program language) |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | General Books |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Relator term | author. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc | Includes bibliographical references and index. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| General subdivision | Statistical methods. |
| 650 #2 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| General subdivision | Statistics. |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| General subdivision | Statistical methods. |
| Source of heading or term | fast |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Source of heading or term | fast |
| 9 (RLIN) | 4 |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) | |
| a | 0 |
| b | ibc |
| c | copycat |
| d | 2 |
| e | ncip |
| f | 20 |
| g | y-gencatlg |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Home library | Location | Shelving location | Date of Cataloging | Total Checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | Non-fiction | CUTN Central Library | CUTN Central Library | Medicine, Technology & Management | 02/04/2025 | 614.407 CAR | 52031 | 02/04/2025 | 02/04/2025 | General Books |