ivonesamplemr Stata package
One-sample Mendelian randomization (MR) / instrumental variable (IV) analyses in Stata.
Latest updates
- September 2025:
- Reran certification scripts under StataNow 19.5
- May 2025:
- Reran certification scripts under StataNow 18.5
- July 2024:
- Amend legend position in
ivmwandivxtileto use the 6 o’clock position as per in Stata 17 and earlier
- Amend legend position in
- January 2024:
- Reran certification scripts under Stata 18.0
- August 2023:
- Added a record of the Stata version in the certification scripts
- April 2023:
- The images in the package website now have accompanying alt text descriptions
- Checked the certification scripts run under the latest Stata 17.0
- Rewrote the website using Quarto
- February 2023:
- Updated the R Markdown code generating the website to use the CRAN version of the Statamarkdown package
- November 2022:
- For an example Mendelian randomization analysis using ivonesamplemr please see Madley-Dowd et al., Maternal vitamin D during pregnancy and offspring autism and autism-associated traits: a prospective cohort study, Molecular Autism, 2022, here
- February 2022:
- Ran cscripts under Stata 17.0
- ivonesamplemr now has a website https://remlapmot.github.io/ivonesamplemr/
Description
The package includes implementations of:
- additive structural mean model: see
help ivasmm - logistic structural mean model: see
help ivlsmm - multiplicative structural mean model: see
help ivmsmm - two-stage predictor substitution estimators: see
ivtsps - two-stage residual inclusion estimators: see
help ivtsri - moving window (a.k.a. sliding/rolling window) versions of these estimators: see
help ivmw - performing estimation within quantiles of the first stage residuals: see
help ivxtile
The ivtsps and ivtsri commands implement the following link functions for the second stage model:
- identity (i.e. linear regression) - for a binary outcome this estimates a causal risk difference
- logadd (log additive, i.e. Poisson/log-binomial regression) and logmult (log multiplicative, i.e. gamma regression) - for a binary outcome these estimate a causal risk ratio
- logit (i.e. logistic regression) - for a binary outcome this estimates a causal odds ratio
Installation
Install the ivonesamplemr package within Stata using
net install github, from("https://haghish.github.io/github/")
github install remlapmot/ivonesamplemrOr use the following code
net install ivonesamplemr, from("https://raw.github.com/remlapmot/ivonesamplemr/main/") replace
do "https://raw.github.com/remlapmot/ivonesamplemr/main/dependency.do"Launch the main package helpfile with
help ivonesamplemrTo check for an update to the package run within Stata
adoupdate ivonesamplemr, updateUninstall the package within Stata using
ado uninstall ivonesamplemr