MVIVW-class function

MVIVW Class

An object containing the estimates produced using the multivariable inverse-variance weighted (IVW) method as well as various statistics. class

Slots

• Model: The model used for estimation: random-effects ("random") or fixed-effect ("fixed"). The default option ("default") is to use a fixed-effect model when there are three or fewer genetic variants, and a random-effects model when there are four or more. The (multiplicative) random-effects model allows for heterogeneity between the causal estimates targeted by the genetic variants by allowing over-dispersion in the regression model. Under-dispersion is not permitted (in case of under-dispersion, the residual standard error is set to 1, as in a fixed-effect analysis).
• Exposure: The names of the exposure variables.
• Outcome: The name of the outcome variable.
• Robust: Whether robust regression was used in the regression model relating the genetic associations with the outcome and those with the exposure.
• Correlation: The matrix of correlations between genetic variants.
• Estimate: The causal estimates from the inverse-variance weighted method.
• StdError: The standard errors associated with Estimate.
• CILower: The lower bounds of the confidence interval for Estimate based on StdError.
• CIUpper: The upper bounds of the confidence interval for Estimate based on StdError.
• Alpha: The significance level used in constructing the confidence interval (default is 0.05).
• Pvalue: P-value associated with the causal estimate.
• SNPs: The number of SNPs that were used in the calculation.
• RSE: The estimated residual standard error from the regression model.
• Heter.Stat: Heterogeneity statistic (Cochran's Q statistic) and associated p-value: the null hypothesis is that all genetic variants estimate the same causal parameter; rejection of the null is an indication that one or more variants may be pleiotropic.
• CondFstat: Conditional F statistics: An approximation of the first-stage conditional F statistics for all variants based on the summarized data. This represents the instrument strength for each exposure conditional on other exposures in the model. This is only reported if the sample sizes for the genetic associations with the exposures are provided.