umx_make_MR_data: Simulate Mendelian Randomization data

In umx: Structural Equation Modeling and Twin Modeling in R

Simulate Mendelian Randomization data

Description

umx_make_MR_data returns a dataset containing 4 variables: A variable of interest (Y), a putative cause (X), a qtl (quantitative trait locus) influencing X, and a confounding variable (U) affecting both X and Y.

Usage

umx_make_MR_data(
  nSubjects = 1000,
  Vqtl = 0.02,
  bXY = 0.1,
  bUX = 0.5,
  bUY = 0.5,
  pQTL = 0.5,
  seed = 123
)

Arguments

nSubjects	Number of subjects in sample
Vqtl	Variance of QTL affecting causal variable X (Default 0.02)
bXY	Causal effect of X on Y (Default 0.1)
bUX	Confounding effect of confounder 'U' on X (Default 0.5)
bUY	Confounding effect of confounder 'U' on Y (Default 0.5)
pQTL	Decreaser allele frequency (Default 0.5)
seed	value for the random number generator (Default 123)

Details

The code to make these Data. Modified from Dave Evans 2016 Boulder workshop talk.

Value

- data.frame

See Also

umx_make_TwinData

Other Data Functions: noNAs(), prolific_anonymize(), prolific_check_ID(), prolific_read_demog(), umxFactor(), umxHetCor(), umx_as_numeric(), umx_cont_2_quantiles(), umx_lower2full(), umx_make_TwinData(), umx_make_fake_data(), umx_make_raw_from_cov(), umx_merge_randomized_columns(), umx_polychoric(), umx_polypairwise(), umx_polytriowise(), umx_read_lower(), umx_rename(), umx_reorder(), umx_score_scale(), umx_select_valid(), umx_stack(), umx_strings2numeric(), umx

Examples

df = umx_make_MR_data(10000)
str(df)
## Not run: 
m1 = umxTwoStage(Y ~ X, ~qtl, data = df)
plot(m1)

## End(Not run)

umx documentation built on Nov. 17, 2023, 1:07 a.m.