MVLasso-class function

MRMVLasso class

An object containing the estimates produced using the multivariable MR-Lasso method as well as various statistics. class

Slots

• Exposure: The names of the exposure variables.
• Outcome: The name of the outcome variable.
• Orientate: The number of the risk factor that genetic associations are orientated to. The default value is 1, meaning that genetic associations with the first risk factor are set to be positive.
• Estimate: The causal estimates from the multivariable MR-Lasso method.
• StdError: The standard errors associated with Estimate.
• CILower: The lower bounds of the confidence intervals for Estimate based on StdError.
• CIUpper: The upper bounds of the confidence intervals for Estimate based on StdError.
• Alpha: The significance level used in constructing the confidence interval (default is 0.05).
• Pvalue: P-values associated with the causal estimates from the multivariable MR-Lasso method.
• SNPs: The number of SNPs used in the calculation.
• RegEstimate: The estimates from the regularized regression model used in the multivariable MR-Lasso method.
• RegIntercept: The intercept estimates from the regularized regression model used in the multivariable MR-Lasso method. An intercept estimate of zero identifies the corresponding genetic variant as a valid instrument. Genetic variants with non-zero intercept estimates will be excluded from the MR-Lasso method, which is obtained as a post-lasso estimator.
• Valid: The number of genetic variants that have been identified as valid instruments.
• ValidSNPs: The names of genetic variants that have been identified as valid instruments.
• Lambda: The value of the tuning parameter used to compute RegEstimate (default is to calulate Lambda using the heterogeneity stopping rule).