The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. mice 1.0 introduced predictor selection, passive imputation and automatic pooling. This article documents mice, which extends the functionality of mice 1.0 in several ways. In mice, the analysis of imputed data is made completely general, whereas the range of models under which pooling works is substantially extended. mice adds new functionality for imputing multilevel data, automatic predictor selection, data handling, post-processing imputed values, specialized pooling routines, model selection tools, and diagnostic graphs. Imputation of categorical data is improved in order to bypass problems caused by perfect prediction. Special attention is paid to transformations, sum scores, indices and interactions using passive imputation, and to the proper setup of the predictor matrix. mice can be downloaded from the Comprehensive R Archive Network. This article provides a hands-on, stepwise approach to solve applied incomplete data problems.

/pdf/mice-multivariate-imputation-by-chained-equations-in-r-2cffzza5jj.pdf

mice: Multivariate Imputation by Chained Equations in R

The world report on violence and health.

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(08)61690-6.pdf

Closing the gap in a generation: health equity through action on the social determinants of health

Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins.

Statistical analysis of data sets with missing values is a pervasive problem for which standard methods are of limited value. The first edition of Statistical Analysis with Missing Data has been a standard reference on missing-data methods. Now, reflecting extensive developments in Bayesian methods for simulating posterior distributions, this Second Edition by two acknowledged experts on the subject offers a thoroughly up-to-date, reorganized survey of current methodology for handling missing-data problems.

Statistical Analysis with Missing Data

ContextDespite calls for wider national implementation of an integrated approach
to trauma care, the effectiveness of this approach at a regional or state
level remains unproven.ObjectiveTo determine whether implementation of an organized system of trauma
care reduces mortality due to motor vehicle crashes.DesignCross-sectional time-series analysis of crash mortality data collected
for 1979 through 1995 from the Fatality Analysis Reporting System.SettingAll 50 US states and the District of Columbia.SubjectsAll front-seat passenger vehicle occupants aged 15 to 74 years.Main Outcome MeasuresRates of death due to motor vehicle crashes compared before and after
implementation of an organized trauma care system. Estimates are based on
within-state comparisons adjusted for national trends in crash mortality.ResultsTen years following initial trauma system implementation, mortality
due to traffic crashes began to decline; about 15 years following trauma system
implementation, mortality was reduced by 8% (95% confidence interval [CI],
3%-12%) after adjusting for secular trends in crash mortality, age, and the
introduction of traffic safety laws. Implementation of primary enforcement
of restraint laws and laws deterring drunk driving resulted in reductions
in crash mortality of 13% (95% CI, 11%-16%) and 5% (95% CI, 3%-7%), respectively,
while relaxation of state speed limits increased mortality by 7% (95% CI,
3%-10%).ConclusionsOur data indicate that implementation of an organized system of trauma
care reduces crash mortality. The effect does not appear for 10 years, a finding
consistent with the maturation and development of trauma triage protocols,
interhospital transfer agreements, organization of trauma centers, and ongoing
quality assurance.

https://jamanetwork.com/journals/jama/articlepdf/192607/JOC91294.pdf

The effect of organized systems of trauma care on motor vehicle crash mortality.

When a study outcome is rare in all strata used for an analysis, the odds ratio estimate of causal effects will approximate the risk ratio; therefore, odds ratios from most case-control studies can be interpreted as risk ratios. However, if a study outcome is common, the odds ratio will be further from 1 than the risk ratio. There is debate regarding the merits of risk ratios compared with odds ratios for the analysis of trials and cohort and cross-sectional studies with common outcomes. Odds ratios are conveniently symmetrical with regard to the outcome definition; the odds ratio for outcome Y is the inverse of the odds ratio for the outcome not Y. Risk ratios lack this symmetry, so it may be necessary to present 1 risk ratio for outcome Y and another for outcome not Y. Risk ratios, but not odds ratios, have a mathematical property called collapsibility; this means that the size of the risk ratio will not change if adjustment is made for a variable that is not a confounder. Because of collapsibility, the risk ratio, assuming no confounding, has a useful interpretation as the ratio change in average risk due to exposure among the exposed. Because odds ratios are not collapsible, they usually lack any interpretation either as the change in average odds or the average change in odds (the average odds ratio).

https://jamanetwork.com/journals/jamapediatrics/articlepdf/381459/pra80010_438_445.pdf

The relative merits of risk ratios and odds ratios.

Chlamydia pneumoniae TWAR has been associated with coronary heart disease by seroepidemiologic studies and direct detection of the organism in atheromatous lesions of coronary arteries and aorta. In this study, 38 fresh tissue specimens from patients with coronary artery lesions that were treated by directional coronary atherectomy were tested for C. pneumoniae. Twenty-three specimens were from patients with primary lesions and 15 were from patients with restenoses. C. pneumoniae was detected by polymerase chain reaction (PCR), immunocytochemical stain (ICC), or both in 20 of 38 specimens. Using cell identity markers, the organism was localized to macrophages. Ultrastructural evidence of the organism was found in the 2 specimens examined by transmission electron microscopy, which were also positive by both ICC and PCR. C. pneumoniae was found more frequently in tissues from restenoses than in primary lesions (P = .17). There was no relation between the frequency of detection of the organism and C. pneumoniae-specific antibody titers.

Detection of Chlamydia pneumoniae TWAR in Human Coronary Atherectomy Tissues

The risk ratio can be a useful statistic for summarizing the results of cross-sectional, cohort, and randomized trial studies. I discuss several methods for estimating adjusted risk ratios and show...

https://journals.sagepub.com/doi/pdf/10.1177/1536867X0900900201

Methods for Estimating Adjusted Risk Ratios

OBJECTIVES: The purpose of this study was to determine whether purchase of a handgun from a licensed dealer is associated with the risk of homicide or suicide and whether any association varies in relation to time since purchase. METHODS: A case-control study was done among the members of a large health maintenance organization. Case subjects were the 353 suicide victims and 117 homicide victims among the members from 1980 through 1992. Five control subjects were matched to each case subject on age, sex, and zip code of residence. Handgun purchase information was obtained from the Department of Licensing. RESULTS: The adjusted relative risk of suicide was 1.9 (95% confidence interval [CI] = 1.4, 2.5) for persons with a history of family handgun purchase from a registered dealer. The adjusted relative risk for homicide, given a history of family handgun purchase, was 2.2 (95% CI = 1.3, 3.7). For both suicide and homicide, the elevated relative risks persisted for more than 5 years after the purchase. CONCL...

The association between the purchase of a handgun and homicide or suicide.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Peter Cummings

Author Tools

Chat about Author