Conduct a meta-analysis. MetaNSUE is a meta-analytic method that allows an unbiased inclusion of studies with Non-statistically Significant Unreported Effects (NSUEs).
meta(x, ...)# S3 method for nsue
meta(x, formula = ~1, hypothesis = NULL,
n.imp = 500, maxiter = 200, tol = 1e-06, ...)
meta
returns an object of class "meta.nsue"
, which is a list containing the following components:
information required for y2var
, mi
and / or backtransf
.
a function to derive the variances of the effect sizes.
a function to multiply impute effect sizes.
a function to back-transform the effect sizes.
a description of the effect-size measure used.
the labels of the studies.
a list with the known effect sizes and their indexs.
a list with the imputations of NSUEs and their indexs.
a list with the formula, matrix and coefficients of the model.
a list with \(\tau^2\), \(H^2\), \(I^2\) and Q test.
the matrixs and coefficients of the hypothesis.
The functions print
and summary
may be used to print the details or a summary of the results. The generic accessor functions coefficients
, fitted.values
and residuals
extract various useful features of the value returned by meta
.
an object of class "nsue"
.
an object of class "formula"
: a symbolic description of the model to be fitted.
a hypothesis, or NULL to test the main coefficient of the model.
number of imputations of NSUEs.
maximum number of iterations in the REML estimation of \(\tau^2\).
tolerance in the REML estimation of \(\tau^2\).
other arguments (currently ignored).
Joaquim Radua
Use nsue
, smc_from_t
, smd_from_t
or zcor_from_r
to create objects of class "nsue"
.
Models for meta
and leave1out
are specified symbolically. The formula
is a series of terms which specify a linear predictor for x
. A formula specification of the form first + second
indicates a multiple regression by first
and second
. A specification of the form first:second
indicates the interaction of first
with second
. The specification first*second
is the same as first + second + first:second
.
Each hypothesis must be a matrix (or vector) giving linear combinations of coefficients by rows.
Radua, J., Schmidt, A., Borgwardt, S., Heinz, A., Schlagenhauf, F., McGuire, P., Fusar-Poli, P. (2015) Ventral striatal activation during reward processing in psychosis. A neurofunctional meta-analysis. JAMA Psychiatry, 72, 1243--51, doi:10.1001/jamapsychiatry.2015.2196.
Albajes-Eizagirre, A., Solanes, A, Radua, J. (2019) Meta-analysis of non-statistically significant unreported effects. Statistical Methods in Medical Research, 28, 3741--54, doi:10.1177/0962280218811349.
nsue
, smc_from_t
, smd_from_t
and zcor_from_r
for creating objects of class "nsue"
.
forest
for plotting forest plots.
funnel
for plotting funnel plots.
metabias
for testing for funnel plot asymmetry.
leave1out
for computing leave-one-out diagnostics.
t <- c(3.4, NA, NA, NA, NA, 2.8, 2.1, 3.1, 2.0, 3.4)
n <- c(40, 20, 22, 24, 18, 30, 25, 30, 16, 22)
meta(smc_from_t(t, n))
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