deft_do

0th

Percentile

Implement deft method

'deft' method is a meta-analytical approach to pool conclusion from multiple studies. More details please see references.

Usage
deft_do(prepare, group_level, method = "FE")
Arguments
prepare

a result data.frame from deft_prepare function or a data.frame contains at least 'trial', 'subgroup', 'yi' and 'sei' these four columns.

group_level

level of subgroup, should be a character vector with length 2 and the reference should put in the first. For example, if you have 'Male' and 'Female' groups and want compare 'Female' with 'Male', then should set c('Male', 'Female').

method

character string specifying whether a fixed- or a random/mixed-effects model should be fitted. A fixed-effects model (with or without moderators) is fitted when using method="FE". Random/mixed-effects models are fitted by setting method equal to one of the following: "DL", "HE", "SJ", "ML", "REML", "EB", "HS", or "GENQ". Default is "REML". See ‘Details’.

Details

About model fit, please see metafor::rma().

Value

a list which class is 'deft'.

References

Fisher, David J., et al. "Meta-analytical methods to identify who benefits most from treatments: daft, deluded, or deft approach?." bmj 356 (2017): j573.

Wang, Shixiang, et al. "The predictive power of tumor mutational burden in lung cancer immunotherapy response is influenced by patients' sex." International journal of cancer (2019).

Aliases
  • deft_do
Examples
# NOT RUN {
data('wang2019')
deft_do(wang2019, group_level = c("Male", "Female"))
# }
Documentation reproduced from package metawho, version 0.1.0, License: GPL-3

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