| IVW-class {MRZero} | R Documentation |
IVW Class
Description
An object containing the estimate produced using the inverse-variance weighted (IVW) method as well as various statistics.
Slots
ModelThe 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).ExposureThe name of the exposure variable.
OutcomeThe name of the outcome variable.
CorrelationThe matrix of correlations between genetic variants.
RobustWhether robust regression was used in the regression model relating the genetic associations with the outcome and those with the exposure.
PenalizedWhether weights in the regression model were penalized for variants with heterogeneous causal estimates.
EstimateThe causal point estimate from the inverse-variance weighted method.
StdErrorThe standard error associated with
Estimate.CILowerThe lower bound of the confidence interval for
Estimatebased onStdError.CIUpperThe upper bound of the confidence interval for
Estimatebased onStdError.AlphaThe significance level used in constructing the confidence interval (default is 0.05).
PvalueP-value associated with the causal estimate.
SNPsThe number of SNPs that were used in the calculation.
RSEThe estimated residual standard error from the regression model.
Heter.StatHeterogeneity 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.
FstatAn approximation of the first-stage F statistic for all variants based on the summarized data.