PIVW-class {MRZero}

PIVW Class

Description

An object containing the estimate produced using the penalized inverse-variance weighted (pIVW) method as well as various statistics.

Slots

Over.dispersion

Should the method consider overdispersion (balanced horizontal pleiotropy)? Default is TRUE.

Boot.Fieller

If Boot.Fieller=TRUE, then the P-value and the confidence interval of the causal effect will be calculated based on the bootstrapping Fieller method. Otherwise, the P-value and the confidence interval of the causal effect will be calculated from the normal distribution. It is recommended to use the bootstrapping Fieller method when Condition (the estimated effective sample size) is smaller than 10. By default, Boot.Fieller=TRUE.

Lambda

The penalty parameter in the pIVW estimator. The penalty parameter plays a role in the bias-variance trade-off of the estimator. It is recommended to choose lambda=1 to achieve the smallest bias and valid inference. By default, lambda=1.

Delta

The z-score threshold for IV selection. By default, delta=0 (i.e., no IV selection will be conducted).

Exposure

The name of the exposure variable.

Outcome

The name of the outcome variable.

Estimate

The causal point estimate from the pIVW estimator.

StdError

The standard error associated with Estimate.

CILower

The lower bound of the confidence interval for Estimate, which is derived from the bootstrapping Fieller method or normal distribution. For the bootstrapping Fieller's interval, if it contains multiple ranges, then lower limits of all ranges will be reported.

CIUpper

The upper bound of the confidence interval for Estimate, which is derived from the bootstrapping Fieller method or normal distribution. For the bootstrapping Fieller's interval, if it contains multiple ranges, then upper limits of all ranges will be reported.

Alpha

The significance level used in constructing the confidence interval (default is 0.05).

Pvalue

P-value associated with the causal estimate from the pIVW estimator.

Tau2

The variance of the balanced horizontal pleiotropy. Tau2 is calculated by using all IVs in the data before conducting the IV selection.

SNPs

The number of SNPs after IV selection.

Condition

The estimated effective sample size. It is recommended to be greater than 5 for the pIVW estimator to achieve reliable asymptotic properties.