hamling: Approximating effective-counts as proposed by Hamling

In dosresmeta: Multivariate Dose-Response Meta-Analysis

Description

Reconstructs the set of pseudo-numbers (or "effective" numbers) of cases and non-cases consistent with the input data (log relative risks). The method was first proposed in 2008 by Hamling.

Usage

hamling(y, v, cases, n, type, data)

Arguments

y	a vector, defining the (reported) log relative risks.
v	a vector, defining the variances of the reported log relative risks.
cases	a vector, defining the number of cases for each exposure level.
n	a vector, defining the total number of subjects for each exposure level. For incidence-rate data n indicates the amount of person-time within each exposure level.
type	a vector (or a character string), specifying the design of the study. Options are cc, ir, and ci, for case-control, incidence-rate, and cumulative incidence data, respectively.
data	an optional data frame (or object coercible by as.data.frame to a data frame) containing the variables in the previous arguments.

Details

The function reconstructs the effective counts corresponding to the multivariable adjusted log relative risks as well as their standard errors. A unique solution is guaranteed by keeping the ratio non-cases to cases and the fraction of unexposed subjects equal to the unadjusted data (Hamling). See the referenced article for a complete description of the algorithm implementation.

Value

A list containing the following

y	mean or standardized mean differences for each treatment level, included the referent one (0 by calculation).
v	variances corresponding to the mean or standardized mean differences for each treatment level, included the referent one (0 by calculation)
S	co(variance) matrix for the non-referent mean or standardized mean differences.

Author(s)

Alessio Crippa, [e-mail]

References

Hamling, J., Lee, P., Weitkunat, R., Ambuhl, M. (2008). Facilitating meta-analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category. Statistics in medicine, 27(7), 954-970.

Orsini, N., Li, R., Wolk, A., Khudyakov, P., Spiegelman, D. (2012). Meta-analysis for linear and nonlinear dose-response relations: examples, an evaluation of approximations, and software. American journal of epidemiology, 175(1), 66-73.

See Also

covar.logrr, grl

Examples

## Loading data
data("alcohol_cvd")

## Obtaining pseudo-counts for the first study (id = 1)
hamling(y = logrr, v = I(se^2), cases = cases, n = n, type = type, 
data = subset(alcohol_cvd, id == 1))
   
## Obtaining pseudo-counts for all study
by(alcohol_cvd, alcohol_cvd$id, function(x)
hamling(y = logrr, v = I(se^2), cases = cases, n = n, type = type, data = x))

## Restructuring the previous results in a matrix
do.call("rbind", by(alcohol_cvd, alcohol_cvd$id, function(x)
   hamling(y = logrr, v = I(se^2), cases = cases, n = n, type = type,
      data = x)))
 

Example output

Loading required package: mvmeta
This is mvmeta 0.4.11. For an overview type: help('mvmeta-package').
This is dosresmeta 2.0.1. For an overview type: help('dosresmeta-package').
            A         N
[1,] 76.95582 257.97205
[2,] 42.73158 168.37362
[3,] 39.45308 132.26428
[4,] 13.97820  33.31917
[5,] 11.31062  22.39601
alcohol_cvd$id: 1
            A         N
[1,] 76.95582 257.97205
[2,] 42.73158 168.37362
[3,] 39.45308 132.26428
[4,] 13.97820  33.31917
[5,] 11.31062  22.39601
------------------------------------------------------------ 
alcohol_cvd$id: 2
             A         N
[1,] 52.913070 177.89752
[2,] 57.763046 267.67141
[3,] 18.556846 147.47628
[4,]  9.994379  53.71185
------------------------------------------------------------ 
alcohol_cvd$id: 3
             A          N
[1,] 41.452972 106.702007
[2,] 22.177529  84.514191
[3,] 10.031247  37.732439
[4,]  2.764006   5.115727
------------------------------------------------------------ 
alcohol_cvd$id: 4
             A         N
[1,] 39.173314 118.44646
[2,] 18.800705  69.52881
[3,] 23.905038  52.87239
[4,]  7.394318  27.89229
------------------------------------------------------------ 
alcohol_cvd$id: 5
             A         N
[1,]  83.90221 236.41751
[2,] 112.61985 480.81420
[3,]  22.27598 118.43150
[4,]  15.84923  48.54299
------------------------------------------------------------ 
alcohol_cvd$id: 6
              A         N
[1,] 194.793723 513.74259
[2,]  51.583855 170.05696
[3,]   8.465255  22.55150
[4,]   5.940072  20.34565
               A          N
 [1,]  76.955815 257.972052
 [2,]  42.731577 168.373625
 [3,]  39.453079 132.264284
 [4,]  13.978196  33.319167
 [5,]  11.310618  22.396014
 [6,]  52.913070 177.897518
 [7,]  57.763046 267.671412
 [8,]  18.556846 147.476283
 [9,]   9.994379  53.711849
[10,]  41.452972 106.702007
[11,]  22.177529  84.514191
[12,]  10.031247  37.732439
[13,]   2.764006   5.115727
[14,]  39.173314 118.446457
[15,]  18.800705  69.528810
[16,]  23.905038  52.872387
[17,]   7.394318  27.892294
[18,]  83.902213 236.417513
[19,] 112.619853 480.814195
[20,]  22.275982 118.431499
[21,]  15.849227  48.542986
[22,] 194.793723 513.742595
[23,]  51.583855 170.056958
[24,]   8.465255  22.551500
[25,]   5.940072  20.345652

dosresmeta documentation built on May 2, 2019, 6:30 a.m.