These function calculate various effect sizes and output objects of class "nsue", ready to be used by meta and leave1out.
smc_from_t(t, n, alpha = 0.05, labels = "study", rm.r = 0.3)
smd_from_t(t, n1, n2, alpha = 0.05, labels = "study", rm.r = 0.3)
z_from_r(r, n, alpha = 0.05, labels = "study", rm.r = 0.3)
r_in_smd_from_t_means_and_sds1(t,
n1, mean1.pre, sd1.pre, mean1.post, sd1.post,
n2, mean2.pre, sd2.pre, mean2.post, sd2.post,
alpha = 0.05, labels = "study", r.range = c(0, 0.99), rm.r = 0.3)
r_in_smd_from_t_means_and_sds2(x, maxiter = 200, tol = 1e-6)a vector to specify the t-values of the studies. Use NA in studies with Non Statistically-Significant Unreported Effects (NSUEs).
a vector to specify the correlation coefficients of the studies. Use NA in studies with Non Statistically-Significant Unreported Effects (NSUEs).
a vector to specify the sample sizes of the studies.
a vector to specify the sample sizes of the first group (e.g. patients) of studies.
a vector to specify the sample sizes of the second group (e.g. controls) of the studies.
a vector to specify the means of the first group (e.g. patients) of the studies before the treatment.
a vector to specify the standard deviations of the first group (e.g. patients) of the studies before the treatment.
a vector to specify the means of the first group (e.g. patients) of the studies after the treatment.
a vector to specify the standard deviations of the first group (e.g. patients) of the studies after the treatment.
a vector to specify the means of the second group (e.g. patients) of the studies before the treatment.
a vector to specify the standard deviations of the second group (e.g. patients) of the studies before the treatment.
a vector to specify the means of the second group (e.g. patients) of the studies after the treatment.
a vector to specify the standard deviations of the second group (e.g. patients) of the studies after the treatment.
a vector to specify the p-value thresholds used in the studies (e.g. 0.05).
a vector to specify the names of the studies.
range of pre-post correlations.
the expected correlation coefficient between repeated-measures.
an object of class "nsue".
maximum number of iterations in the REML estimation of \(\tau^2\).
tolerance in the REML estimation of \(\tau^2\).
smc_from_t, smd_from_t, z_from_r and r_in_smd_from_t_means_and_sds1 return objects of class "nsue".
The function print may be used to print a summary of the results.
An object of class "nsue" is a list containing several of the following components:
the effect-size measure used.
the effect-sizes.
the effect-sizes corresponding to the lower statistical threshold.
the effect-sizes corresponding to the upper statistical threshold.
the variances of the effect sizes.
a constant needed to derive the variances.
a constant needed to derive the variances.
the labels of the studies.
a list with the expected correlation between repeated-measures studies.
Use smc_from_t for calculating the standardized mean changes from the t-values of the paired Student t-tests, e.g. in repeated-measures studies analyzing the amount of change in within a group.
Use smd_from_t for calculating the standardized mean differences from t-values of the two-sample Student t-tests, e.g. in studies comparing a quantitative (normally-distributed) variable between two groups.
Use z_from_r for calculating the Fisher's r-to-z transformed correlations coefficients from the Pearson correlation coefficients (r), e.g. in studies examining the association between two quantitative (normally-distributed) variables.
Use r_in_smd_from_t_means_and_sds1 and meta for estimating the missing pre-post correlations in a meta-analysis of the pre-post differences, e.g. when you only have the means and standard deviations before and after a treatment. Afterwards, use r_in_smd_from_t_means_and_sds2 to conduct the meta-analysis of the pre-post differences. Please see Harrison et al for details.
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.
Harrison, A., Fernandez de la Cruz, L., Enander, J., Radua, J., Mataix-Cols, D. (2016) Cognitive-behavioral therapy for body dysmorphic disorder: A systematic review and meta-analysis of randomized controlled trials. Clinical Psychology Review, in Press.
meta for conducting a meta-analysis.
leave1out for computing leave-one-out diagnostics.
# NOT RUN {
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)
x <- smc_from_t(t, n)
x
meta(x)
# }
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