OverallRiskSummaries {bkmr} R Documentation

## Calculate overall risk summaries

### Description

Compare estimated `h` function when all predictors are at a particular quantile to when all are at a second fixed quantile

### Usage

```OverallRiskSummaries(fit, y = NULL, Z = NULL, X = NULL, qs = seq(0.25,
0.75, by = 0.05), q.fixed = 0.5, method = "approx", sel = NULL)
```

### Arguments

 `fit` An object containing the results returned by a the `kmbayes` function `y` a vector of outcome data of length `n`. `Z` an `n`-by-`M` matrix of predictor variables to be included in the `h` function. Each row represents an observation and each column represents an predictor. `X` an `n`-by-`K` matrix of covariate data where each row represents an observation and each column represents a covariate. Should not contain an intercept column. `qs` vector of quantiles at which to calculate the overall risk summary `q.fixed` a second quantile at which to compare the estimated `h` function `method` method for obtaining posterior summaries at a vector of new points. Options are "approx" and "exact"; defaults to "approx", which is faster particularly for large datasets; see details `sel` selects which iterations of the MCMC sampler to use for inference; see details

### Details

• If `method == "approx"` then calls the function `ComputePostmeanHnew.approx`. In this case, the argument `sel` defaults to the second half of the MCMC iterations.

• If `method == "exact"` then calls the function `ComputePostmeanHnew.exact`. In this case, the argument `sel` defaults to keeping every 10 iterations after dropping the first 50% of samples, or if this results in fewer than 100 iterations, than 100 iterations are kept

For guided examples and additional information, go to https://jenfb.github.io/bkmr/overview.html

[Package bkmr version 0.2.0 Index]