sens_dt {metainc}

Sensitivity analysis (based on decision thresholds) for the Decision Inconsistency and Across-Studies Inconsistency index

Description

Sensitivity analysis on the Decision Inconsistency index and the Across-Studies Inconsistency index based on a range of decision thresholds distinguishing meaningful versus trivial effects. It is applicable only to meta-analyses with binary outcome data (effect size measures expressed as risk ratios, odds ratios or hazard ratios).

Usage

sens_dt(x, br = NULL, min1, max1, min2, max2, sm, by = 1, scale = 1000)

heatplot(x, limits1 = NULL, limits2 = NULL, ...)

Arguments

x

An R object created with getsamples or a matrix containing the samples of the effect sizes of primary studies. Note that log-transformed effect sizes must be provided (e.g., log odds ratios instead of odds ratios).

br

Baseline risk.

min1

A single numeric defining the lowest value for the lower decision threshold. Must be lower than max1, min2 and max2.

max1

A single numeric defining the highest value for the lower decision threshold. Must be higher than min1, but lower than min2 and max2.

min2

A single numeric defining the lowest value for the higher decision threshold. Must be higher than min1 and max1, but lower than max2.

max2

A single numeric defining the highest value for the higher decision threshold. Must be higher than min1, max1 and min2.

sm

A character string indicating the summary measure used in primary studies (either sm = "OR", sm = "RR" or sm = "HR").

by

Increment of the sequences from min1 to max1 and min2 to max2.

scale

The number of people per which absolute decision thresholds are provided (default: 1000, i.e., absolute decision threshold values are defined per 1000 people).

limits1

Limits for the colour range in the heatplot showing the Decision Inconsistency index.

limits2

Limits for the colour range in the heatplot showing the Across-Studies Inconsistency index.

...

Additional graphical arguments (ignored).

Details

Computes the Decision Inconsistency index (DI) and the Across-Studies Inconsistency index (ASI) across a range of decision thresholds distinguishing meaningful vs trivial effects. This function can only be applied to dichotomous outcomes expressed as (log-) odds ratio, risk ratio and hazard ratio. Graphical representations can be obtained using the heatplot function.

Value

A data frame containing

dt1

Lower decision threshold

dt2

Higher decision threshold

ASI

Decision Inconsistency index for each combination of decision thresholds

DI

Across-Studies Inconsistency index for each combination of decision thresholds

Author(s)

Bernardo Sousa-Pinto [e-mail], Guido Schwarzer [e-mail]

References

Schunemann HJ, Higgins JPT, Vist GE, et al. (2019). “Completing ‘Summary of findings’ tables and grading the certainty of the evidence.” Cochrane Handbook for Systematic Reviews of Interventions, 375–402.

Skoetz N, Goldkuhle M, van Dalen EC, et al. (2020). “GRADE guidelines 27: how to calculate absolute effects for time-to-event outcomes in summary of findings tables and Evidence Profiles.” Journal of Clinical Epidemiology, 118, 124–131.

Examples

data(anticoagulation)
dis <- sens_dt(log(anticoagulation),
  br = 0.5, min1 = -20, max1 = -10, min2 = 10, max2 = 20, sm = "or")
#
head(dis)
summary(dis$DI)
summary(dis$ASI)

heatplot(dis)