Description Usage Arguments Value Author(s) Examples

mvshape fits a multivariate meta-analysis for groups of the exposure (e.g. deciles).

1 2 |

`y` |
outcome. |

`x` |
exposure. |

`covar` |
data.frame with covariates. |

`study` |
study variable. |

`ngrp` |
number of quantiles of the exposure. |

`refgrp` |
reference group. |

`family` |
the glm family (options: gaussian and binomial). |

`float` |
floating point variances. |

`method` |
meta-analysis method. |

List of multivariate meta-analysis results for each group.

`results` |
data.frame of results: q is the quantile group, xbeta is the mean of x in each quantile, xse is the standard error of the mean of x in each quantile, beta is the regression coefficient of association between y and each quantile of x, se is the standard error of the regression coefficient of association between y and each quantile of x |

`varcor` |
variance-covariance matrix |

`xmin` |
miniumum value of the exposure |

`xmax` |
maximum value of the exposure |

`family` |
family used in the analysis |

James R Staley <[email protected]>

1 2 3 4 5 6 7 8 9 10 | ```
### Data
y <- rnorm(5000)
x <- rnorm(5000,10,1)
c1 <- rbinom(5000,1,0.5)
c2 <- rnorm(5000)
covar <- data.frame(c1=c1, c2=c2)
study <- c(rep("study1",1000),rep("study2",1000),rep("study3",1000),rep("study4",1000),rep("study5",1000))
### Analyses
res <- mvshape(y=y, x=x, covar=covar, study=study, family="gaussian")
``` |

jrs95/mvshape documentation built on Feb. 14, 2019, 7:33 p.m.

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