MAIVE (version 0.2.4)

maive: R code for MAIVE

Description

R package for MAIVE: "Spurious Precision in Meta-Analysis of Observational Research" by Zuzana Irsova, Pedro Bom, Tomas Havranek, Petr Cala, and Heiko Rachinger.

Usage

maive(
  dat,
  method,
  weight,
  instrument,
  studylevel,
  SE,
  AR,
  first_stage = 0L,
  estimate = NULL,
  se = NULL,
  n = NULL,
  study_id = NULL,
  seed = 123
)

Value

• beta: MAIVE meta-estimate

• SE: MAIVE standard error

• F-test: heteroskedastic robust F-test of the first step instrumented SEs

• beta_standard: point estimate from the method chosen

• SE_standard: standard error from the method chosen

• Hausman: Hausman type test: comparison between MAIVE and standard version

• Chi2: 5

• SE_instrumented: instrumented standard errors

• AR_CI: Anderson-Rubin confidence interval for weak instruments

• pub bias p-value: p-value of test for publication bias / p-hacking based on instrumented FAT

• egger_coef: Egger Coefficient (PET estimate)

• egger_se: Egger Standard Error (PET standard error)

• egger_boot_ci: Confidence interval for the Egger coefficient using the selected resampling scheme

• egger_ar_ci: Anderson-Rubin confidence interval for the Egger coefficient (when available)

• is_quadratic_fit: Details on quadratic selection and slope behaviour

• boot_result: Boot result

• slope_coef: Slope coefficient

• petpeese_selected: Which model (PET or PEESE) was selected when method=3 (NA otherwise)

• peese_se2_coef: Coefficient on SE^2 when PEESE is the final model (NA otherwise)

• peese_se2_se: Standard error of the PEESE SE^2 coefficient (NA otherwise)

Arguments

dat

Data frame with columns bs, sebs, Ns, study_id (optional).

method

1 FAT-PET, 2 PEESE, 3 PET-PEESE, 4 EK.

weight

0 no weights, 1 standard weights, 2 MAIVE adjusted weights, 3 study weights.

instrument

1 yes, 0 no.

studylevel

Correlation at study level: 0 none, 1 fixed effects, 2 cluster.

SE

SE estimator: 0 CR0 (Huber-White), 1 CR1 (Standard empirical correction), 2 CR2 (Bias-reduced estimator), 3 wild bootstrap.

AR

Anderson Rubin corrected CI for weak instruments (available for unweighted and MAIVE-adjusted weight versions of PET, PEESE, PET-PEESE, not available for fixed effects): 0 no, 1 yes.

first_stage

First-stage specification for the variance model: 0 levels, 1 log.

estimate

Optional column name to use instead of 'bs'

se

Optional column name to use instead of 'sebs'

n

Optional column name to use instead of 'Ns'

study_id

Optional column name for study identifiers

seed

Seed for the wild bootstrap when SE = 3. Use NULL to avoid setting a seed (results depend on the current RNG state). Default is 123 for historical reproducibility.

Details

Guided, interactive workflow available at https://www.easymeta.org.

Data dat can be imported from an Excel file via: dat <- read_excel("inputdata.xlsx") or from a csv file via: dat <- read.csv("inputdata.csv") It should contain:

• Estimates: bs

• Standard errors: sebs

• Number of observations: Ns

• Optional: study_id

Default option for MAIVE: MAIVE-PET-PEESE, unweighted, instrumented, cluster SE, wild bootstrap, AR.

Examples

dat <- data.frame(
  bs = c(0.5, 0.45, 0.55, 0.6),
  sebs = c(0.25, 0.2, 0.22, 0.27),
  Ns = c(50, 80, 65, 90)
)

result <- maive(dat,
  method = 3, weight = 0, instrument = 1,
  studylevel = 0, SE = 0, AR = 0, first_stage = 0
)