metafor: llplot – R documentation

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llplot

Likelihood Plot of a Parameter Corresponding to an Effect Size or Outcome Measure

Description

Function to plot the likelihood of a certain parameter corresponding to an effect size or outcome measure given the study data.

Usage

llplot(measure, yi, vi, sei, ai, bi, ci, di, n1i, n2i, data, subset, drop00=TRUE,
       xvals=1000, xlim, ylim, xlab, ylab, scale=TRUE,
       lty, lwd, col, level=99.99, refline=0, ...)

Arguments

`measure`	a character string indicating for which effect size or outcome measure the likelihoods should be calculated. See ‘Details’ for possible options and how the data should be specified.
`yi`	vector with the observed effect sizes or outcomes.
`vi`	vector with the corresponding sampling variances.
`sei`	vector to specify the corresponding standard.
`ai`	vector to specify the 2x2 table frequencies (upper left cell).
`bi`	vector to specify the 2x2 table frequencies (upper right cell).
`ci`	vector to specify the 2x2 table frequencies (lower left cell).
`di`	vector to specify the 2x2 table frequencies (lower right cell).
`n1i`	vector to specify the group sizes or row totals (first group/row).
`n2i`	vector to specify the group sizes or row totals (second group/row).
`data`	optional data frame containing the variables given to the arguments above.
`subset`	optional (logical or numeric) vector indicating the subset of studies that should be included in the plot.
`drop00`	logical indicating whether studies with no cases (or only cases) in both groups should be dropped. See ‘Details’.
`xvals`	integer specifying for how many distinct values the likelihood should be evaluated.
`xlim`	x-axis limits. If unspecified, the function tries to set the x-axis limits to some sensible values.
`ylim`	y-axis limits. If unspecified, the function tries to set the y-axis limits to some sensible values.
`xlab`	title for the x-axis. If unspecified, the function tries to set an appropriate axis title.
`ylab`	title for the y-axis. If unspecified, the function tries to set an appropriate axis title.
`scale`	logical indicating whether the likelihood values should be scaled, so that the total area under each curve is (approximately) equal to 1.
`lty`	the line types (either a single value or a vector of length k). If unspecified, the function sets the line types according to some characteristics of the likelihood function. See ‘Details’.
`lwd`	the line widths (either a single value or a vector of length k). If unspecified, the function sets the widths according to the sampling variances (so that the line is thicker for more precise studies and vice-versa).
`col`	the line colors (either a single value or a vector of length k). If unspecified, the function uses various shades of gray according to the sampling variances (so that darker shades are used for more precise studies and vice-versa).
`level`	numerical value between 0 and 100 specifying the plotting limits for each likelihood line in terms of the confidence interval (the default is 99.99).
`refline`	value at which a vertical ‘reference’ line should be drawn (the default is 0). The line can be suppressed by setting this argument to `NA`.
`...`	other arguments.

Details

At the moment, the function only accepts measure="GEN" or measure="OR".

For measure="GEN", one must specify arguments yi for the observed effect sizes or outcomes and vi for the corresponding sampling variances (instead of specifying vi, one can specify the standard errors via the sei argument). The function then plots the likelihood of the true outcome based on a normal sampling distribution with observed outcome as given by yi and variance as given by vi for each study.

For measure="OR", one must specify arguments ai, bi, ci, and di, which denote the cell frequencies of the 2x2 tables. Alternatively, one can specify ai, ci, n1i, and n2i. See escalc function for more details. The function then plots the likelihood of the true log odds ratio based on the non-central hypergeometric distribution for each 2x2 table. Since studies with no cases (or only cases) in both groups have a flat likelihood and are not informative about the odds ratio, they are dropped by default (i.e., drop00=TRUE) and are hence not drawn (if drop00=FALSE, these likelihood are indicated by dotted lines). For studies that have a single zero count, the MLE of the odds ratio is infinite and these likelihoods are indicated by dashed lines.

Author(s)

Wolfgang Viechtbauer wvb@metafor-project.org http://www.metafor-project.org/

References

van Houwelingen, H. C., Zwinderman, K. H., & Stijnen, T. (1993). A bivariate approach to meta-analysis. Statistics in Medicine, 12, 2273–2284.

Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1–48. https://www.jstatsoft.org/v036/i03.

Examples

### calculate log risk ratios and corresponding sampling variances
dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)

### draw likelihoods
llplot(measure="GEN", yi=yi, vi=vi, data=dat, lwd=1, refline=NA, xlim=c(-3,2))

### create plot (Figure 2 in van Houwelingen, Zwinderman, & Stijnen, 1993)
llplot(measure="OR", ai=b.xci, n1i=nci, ci=b.xti, n2i=nti, data=dat.collins1985a,
       lwd=1, refline=NA, xlim=c(-4,4), drop00=FALSE)

metafor

Meta-Analysis Package for R

v2.4-0

GPL (>= 2)

Authors

Wolfgang Viechtbauer [aut, cre] (<https://orcid.org/0000-0003-3463-4063>)

Initial release

2020-03-19