Biostatistics for Biomedical Research

Author

Affiliation

Department of Biostatistics
School of Medicine
Vanderbilt University

Published

September 22, 2023

flowchart LR
Q[Research<br>Question] --> M[Measurements] --> D[Design] --> Ac[Data<br>Acquisition] --> Des[Description] --> A[Analysis] --> I[Interpretation] & Pred[Prediction]
Pred --> V[Validation]
I --> K[New Knowledge] & Dec[Decisions]

Preface

The book is aimed at exposing biomedical researchers to modern biostatistical methods and statistical graphics, highlighting those methods that make fewer assumptions, including nonparametric statistics and robust statistical measures. In addition to covering traditional estimation and inferential techniques, the course contrasts those with the Bayesian approach, and also includes several components that have been increasingly important in the past few years, such as challenges of high-dimensional data analysis, modeling for observational treatment comparisons, analysis of differential treatment effect (heterogeneity of treatment effect), statistical methods for biomarker research, medical diagnostic research, and methods for reproducible research. A glossary of statistical terms for non-statisticians is here. R Workflow is a useful companion to this book, especially for those needing to manipulate data in preparation for analysis and for those interested in embedding statistical analyses in state-of-the-art reproducible reports.

BBR course

For information about adding annotations, comments, and questions inside the text click here: Comments

Symbols Used in the Right Margin of the Text

Blue symbols in the right margin starting with ABD designate section numbers (and occasionally page numbers preceeded by $p$) in The Analysis of Biological Data, Second Edition by MC Whitlock and D Schluter, Greenwood Village CO, Roberts and Company, 2015.
Right blue symbols starting with RMS designate section numbers in Regression Modeling Strategies, 2nd ed. by FE Harrell, Springer, 2015.
in the right margin is a hyperlink to a YouTube video related to the subject.
is a hyperlink to the discussion topic in datamethods.org devoted to the specific YouTube video session. You can go directly to the discussion about session n by going to bit.ly/datamethods-bbrn. Some of the sessions on YouTube also had live chat which you can select to replay while watching the video.
Boxed blue text in the right margin represents a mnemonic key for linking to discussions about that section in datamethods. Anyone starting a new discussion about a topic related to the section should include the mnemonic somewhere in the posting. When you click on the blue boxed text the datamethods search result of all topics containing that mnemonic will appear, and the user can navigate from it to the topic of interest to read or add content.
An audio player symbol indicates that narration elaborating on the notes is available for the section. Red letters and numbers in the right margin are cues referred to within the audio recordings.
blog in the right margin is a link to a blog entry that further discusses the topic.

Other Information

BBR course
YouTube channel BBRcourse for these notes
Discussion board about the overall course
Go directly to a YouTube video for BBR Session n by going to bit.ly/yt-bbrn
Glossary of statistical terms
Datamethods discussion board
Statistical papers written for clinical researchers
Statistical Thinking blog
Statistical Thinking News

Acknowledgement

This material grew largely out of teaching clinical scholars and in Master of Science in Clinical Investigation programs at Duke University, University of Virginia, and Vanderbilt University. I benefitted immensely from lecture notes from colleagues such as Kerry Lee of Duke University. Thanks also goes to Vanderbilt Biostatistics colleague James C. Slaughter who made several contributions to an earlier version of the book at hbiostat.org/doc/bbr.pdf.

Update History

Date	Sections	Changes
2023-09-22	20.3.4	New section on bootstrapping importantance ranks using one-at-a-time feature modeling
2023-09-16	20.3.3	New section on estimation of correlation matrices
2023-07-28	7.9	New section on using models for paired data
2023-07-26	7.8	Added example of ordinal model for 2-way ANOVA
2023-06-22	13	Added big picture
2023-06-16	13.5	Added more to section on how many covariates to add
2023-04-27	7.12	New section on sample size for ECDF
2023-04-05	14.4.2	Added confidence bands
2023-03-30	20.3.1	Fixed bug in simulation graphics
2023-03-29	3.2.1	New link to clinical trial design resource
2023-03-13	21	New subsection on the decline effect
2023-02-19	3.9	Added link to resources for learning probability
2022-12-29	4.3.5	Added single-axis nomogram example
2022-12-28		Started to add old study questions to end of selected chapters
2022-12-03	14.4.2	New section with real example of misleading change score
2022-11-27	14.4.4	New section on importance of current status vs. baseline status and irrelevance of change for patients
2022-08-02	19	Quote about weaknesses in sens and spec; link to CrossValidated discussion
2022-08-31	8.5.2	New material on sample size vs. P(correct sign on r)

<img src="logo.png" width=70%> ```{mermaid} %%| column: screen-inset-right %%| fig-width: 8 flowchart LR Q[Research Question] --> M[Measurements] --> D[Design] --> Ac[Data Acquisition] --> Des[Description] --> A[Analysis] --> I[Interpretation] & Pred[Prediction] Pred --> V[Validation] I --> K[New Knowledge] & Dec[Decisions] ``` # Preface {.unnumbered} The book is aimed at exposing biomedical researchers to modern biostatistical methods and statistical graphics, highlighting those methods that make fewer assumptions, including nonparametric statistics and robust statistical measures. In addition to covering traditional estimation and inferential techniques, the course contrasts those with the Bayesian approach, and also includes several components that have been increasingly important in the past few years, such as challenges of high-dimensional data analysis, modeling for observational treatment comparisons, analysis of differential treatment effect (heterogeneity of treatment effect), statistical methods for biomarker research, medical diagnostic research, and methods for reproducible research. A glossary of statistical terms for non-statisticians is [here](http://hbiostat.org/glossary).[[BBR course](https://hbiostat.org/bbrc)]{.aside} [`R Workflow`](https://hbiostat.org/rflow) is a useful companion to this book, especially for those needing to manipulate data in preparation for analysis and for those interested in embedding statistical analyses in state-of-the-art reproducible reports. ```{r include=FALSE} require(Hmisc) getRs('qbookfun.r') ``` For information about adding annotations, comments, and questions inside the text click here: `r hypcomment` ### Symbols Used in the Right Margin of the Text * Blue symbols in the right margin starting with ABD designate section numbers (and occasionally page numbers preceeded by $p$) in _The Analysis of Biological Data, Second Edition_ by MC Whitlock and D Schluter, Greenwood Village CO, Roberts and Company, 2015. * Right blue symbols starting with RMS designate section numbers in _Regression Modeling Strategies, 2nd ed._ by FE Harrell, Springer, 2015. * <img src="movie.png" width="15px"> in the right margin is a hyperlink to a YouTube video related to the subject. * <img src="discourse.png" width="15px"> is a hyperlink to the discussion topic in `datamethods.org` devoted to the specific `YouTube` video session. You can go directly to the discussion about session `n` by going to `bit.ly/datamethods-bbrn`. Some of the sessions on `YouTube` also had live chat which you can select to replay while watching the video. * Boxed blue text in the right margin represents a mnemonic key for linking to discussions about that section in [datamethods](http://datamethods.org). Anyone starting a new discussion about a topic related to the section should include the mnemonic somewhere in the posting. When you click on the blue boxed text the `datamethods` search result of all topics containing that mnemonic will appear, and the user can navigate from it to the topic of interest to read or add content. * An audio player symbol indicates that narration elaborating on the notes is available for the section. Red letters and numbers in the right margin are cues referred to within the audio recordings. * blog in the right margin is a link to a blog entry that further discusses the topic. ## Other Information * [BBR course](https://hbiostat.org/bbrc) * YouTube channel [`BBRcourse`](http://bit.ly/yt-bbr) for these notes * [Discussion board about the overall course](http://datamethods.org/t/bbr-video-course) * Go directly to a YouTube video for BBR Session `n` by going to `bit.ly/yt-bbrn` * [Glossary of statistical terms](https://hbiostat.org/glossary) * [Datamethods discussion board](http://datamethods.org) * [Statistical papers written for clinical researchers](https://hbiostat.org/bib) * [Statistical Thinking blog](https://fharrell.com) * [Statistical Thinking News](https://hbiostat.org/news) ## Acknowledgement This material grew largely out of teaching clinical scholars and in Master of Science in Clinical Investigation programs at Duke University, University of Virginia, and Vanderbilt University. I benefitted immensely from lecture notes from colleagues such as Kerry Lee of Duke University. Thanks also goes to Vanderbilt Biostatistics colleague James C. Slaughter who made several contributions to an earlier version of the book at [hbiostat.org/doc/bbr.pdf](https://hbiostat.org/doc/bbr.pdf). ::: {.callout-note collapse="true"} # Update History | Date | Sections | Changes | Thanks To | |:-----|:---------|:--------|:----------| | 2023-09-22 | [-@sec-hdata-oaat] | New section on bootstrapping importantance ranks using one-at-a-time feature modeling | | 2023-09-16 | [-@sec-hdata-rmatrix] | New section on estimation of correlation matrices | | 2023-07-28 | [-@sec-nonpar-pairmodel] | New section on using models for paired data | | 2023-07-26 | [-@sec-nonpar-2way] | Added example of ordinal model for 2-way ANOVA | | 2023-06-22 | [-@sec-ancova] | Added big picture | | 2023-06-16 | [-@sec-ancova-p] | Added more to section on how many covariates to add | | 2023-04-27 | [-@sec-nonpar-ecdf] | New section on sample size for ECDF | | 2023-04-05 | [-@sec-change-ex] | Added confidence bands | | 2023-03-30 | [-@sec-hdata-simor] | Fixed bug in simulation graphics | | 2023-03-29 | [-@sec-overview-scimeth] | New link to clinical trial design resource | | 2023-03-13 | [-@sec-repro] | New subsection on the decline effect | | 2023-02-19 | [-@sec-prob] | Added link to resources for learning probability | | 2022-12-29 | [-@sec-descript-models]| Added single-axis nomogram example | | 2022-12-28 | | Started to add old study questions to end of selected chapters | | 2022-12-03 | [-@sec-change-ex] | New section with real example of misleading change score | | 2022-11-27 | [-@sec-change-current] | New section on importance of current status vs. baseline status and irrelevance of change for patients | | 2022-08-02 | [-@sec-dx] | Quote about weaknesses in sens and spec; link to CrossValidated discussion | | | 2022-08-31 | [-@sec-corr-n] | New material on sample size vs. P(correct sign on r) | | :::