framingham

Data collected over a 24 year study suitable for competing
 risks survival analysis of hypertension and death as a function of smoking.

data

Implements novel nonparametric approaches to address
biases and confounding when comparing treatments or exposures in
observational studies of outcomes. While designed and appropriate for use
in studies involving medicine and the life sciences, the package can be
used in other situations involving outcomes with multiple confounders.
The package implements a family of methods for non-parametric bias correction
when comparing treatments in observational studies, including survival
analysis settings, where competing risks and/or censoring may be present.
The approach extends to bias-corrected personalized predictions of treatment
outcome differences, and analysis of heterogeneity of treatment effect-sizes
across patient subgroups. For further details, please see:
Lauve NR, Nelson SJ, Young SS, Obenchain RL, Lambert CG. LocalControl:
An R Package for Comparative Safety and Effectiveness Research.
Journal of Statistical Software. 2020. p. 1<e2><80><93>32. Available from <doi:10.18637/jss.v096.i04>.

Christophe Lambert

LocalControl

Nonparametric Methods for Generating High Quality Comparative
Effectiveness Evidence

Nicolas R. Lauve

Stuart J. Nelson

S. Stanley Young

Robert L. Obenchain

Melania Pintilie

Martin Kutz

Christophe G. Lambert

framingham function

A data frame with 2316 rows and 11 columns:<dl class="dl-horizontal">
 <dt>female</dt><dd>Sex of the patient. 1=female, 0=male.</dd>
 <dt>totchol</dt><dd>Total cholesterol of patient at study entry.</dd>
 <dt>age</dt><dd>Age of the patient at study entry.</dd>
 <dt>bmi</dt><dd>Patient body mass index.</dd>
 <dt>BPVar</dt><dd>Average units of systolic and diastolic blood pressure above normal: ((SystolicBP-120)/2) + (DiasystolicBP-80)</dd>
 <dt>heartrte</dt><dd>Patient heartrate taken at study entry.</dd>
 <dt>glucose</dt><dd>Patient blood glucose level.</dd>
 <dt>cursmoke</dt><dd>Whether or not the patient was a smoker at the time of study entry.</dd>
 <dt>outcome</dt><dd>Did the patient die, experience hypertension, or leave the study without experiencing either event.</dd>
 <dt>time_outcome</dt><dd>The time at which the patient experienced outcome.</dd>
 <dt>cigpday</dt><dd>Number of cigarettes smoked per day at time of study entry.</dd>
</dl>

Format

Framingham heart study data extract on smoking and hypertension. — framingham

A data frame with 2316 rows and 11 columns:<dl class='dl-horizontal'>
 <dt>female</dt><dd>Sex of the patient. 1=female, 0=male.</dd>
 <dt>totchol</dt><dd>Total cholesterol of patient at study entry.</dd>
 <dt>age</dt><dd>Age of the patient at study entry.</dd>
 <dt>bmi</dt><dd>Patient body mass index.</dd>
 <dt>BPVar</dt><dd>Average units of systolic and diastolic blood pressure above normal: ((SystolicBP-120)/2) + (DiasystolicBP-80)</dd>
 <dt>heartrte</dt><dd>Patient heartrate taken at study entry.</dd>
 <dt>glucose</dt><dd>Patient blood glucose level.</dd>
 <dt>cursmoke</dt><dd>Whether or not the patient was a smoker at the time of study entry.</dd>
 <dt>outcome</dt><dd>Did the patient die, experience hypertension, or leave the study without experiencing either event.</dd>
 <dt>time_outcome</dt><dd>The time at which the patient experienced outcome.</dd>
 <dt>cigpday</dt><dd>Number of cigarettes smoked per day at time of study entry.</dd>
</dl>

Framingham heart study data extract on smoking and hypertension.

framingham: Framingham heart study data extract on smoking and hypertension.

Description

Arguments

Format

References