Risultati

Meta-Analysis

This analysis has terminated, likely due to hitting a resource limit.

Random-Effects Model
	Estimate	se	Z	p	CI Lower Bound	CI Upper Bound
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[3]

Heterogeneity Statistics
Tau	Tau²	I²	H²	R²	df	Q	p
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Model Fit Statistics and Information Criteria
	log-likelihood	Deviance	AIC	BIC	AICc
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.	.	.	.	.	.

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Selection Model Results
Estimate	SE	p-value	CI Lower Bound	CI Upper Bound
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[3]


Test Name	value	p
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Funnel Plot

[3]

Funnel Plot

[3]

Funnel Plot

[3]

Test of Excess Significance \| Significant Findings

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[0]

Test of Excess Significance \| Estimated Power of Tests
Min	Q1	Median	Q3	Max
.	.	.	.	.

[0]

p Curve Plot

Publication bias test p-uniform
Test Statistic		p-value
.		.

Effect size estimation p-uniform
Effect Size Estimate	CI Lower Bound	CI upper Bound	Z	p-value	Number of Significant Studies
.	.	.	.	.	.

Two One-Sided Tests Equivalence Testing
Z-Value Lower Bound	P-Value Lower Bound	Z-Value Upper Bound	P-Value Upper Bound	Lower Limit Confidence Interval TOST	Upper Limit Confidence Interval TOST	LL_CI_ZTEST	Z-Value Upper Limit Confidence Interval TOST
.	.	.	.	.	.	.	.

[0]

Equivalence Test Plot

[0]

Likelihood Plot

[0]

Outlier and Influential Case Diagnostics

Externally Standardized Residual

DFFITS Values

Cook's Distances

Covariance Ratios

Leave-one-out Tau Estimates

Leave-one-out (residual) Heterogeneity Test Statistics

Hat Values

Weights

Q-Q Plot

Meta-Analysis

This analysis has terminated, likely due to hitting a resource limit.

Random-Effects Model
	Estimate	se	Z	p	CI Lower Bound	CI Upper Bound
.	.	.	.	.	.	.
.	.	.	.	.	.	.

[3]

Heterogeneity Statistics
Tau	Tau²	I²	H²	R²	df	Q	p
.	.	.	.	.	.	.	.

Model Fit Statistics and Information Criteria
	log-likelihood	Deviance	AIC	BIC	AICc
.	.	.	.	.	.
.	.	.	.	.	.

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Selection Model Results
Estimate	SE	p-value	CI Lower Bound	CI Upper Bound
.	.	.	.	.

[3]


Test Name	value	p
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.	.	.
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.	.	.

Funnel Plot

[3]

Funnel Plot

[3]

Funnel Plot

[3]

Test of Excess Significance \| Significant Findings

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[0]

Test of Excess Significance \| Estimated Power of Tests
Min	Q1	Median	Q3	Max
.	.	.	.	.

[0]

p Curve Plot

Publication bias test p-uniform
Test Statistic		p-value
.		.

Effect size estimation p-uniform
Effect Size Estimate	CI Lower Bound	CI upper Bound	Z	p-value	Number of Significant Studies
.	.	.	.	.	.

Two One-Sided Tests Equivalence Testing
Z-Value Lower Bound	P-Value Lower Bound	Z-Value Upper Bound	P-Value Upper Bound	Lower Limit Confidence Interval TOST	Upper Limit Confidence Interval TOST	LL_CI_ZTEST	Z-Value Upper Limit Confidence Interval TOST
.	.	.	.	.	.	.	.

[0]

Equivalence Test Plot

[0]

Likelihood Plot

[0]

Outlier and Influential Case Diagnostics

Externally Standardized Residual

DFFITS Values

Cook's Distances

Covariance Ratios

Leave-one-out Tau Estimates

Leave-one-out (residual) Heterogeneity Test Statistics

Hat Values

Weights

Q-Q Plot

Meta-Analysis

This analysis has terminated, likely due to hitting a resource limit.

Random-Effects Model
	Estimate	se	Z	p	CI Lower Bound	CI Upper Bound
.	.	.	.	.	.	.
.	.	.	.	.	.	.

[3]

Heterogeneity Statistics
Tau	Tau²	I²	H²	R²	df	Q	p
.	.	.	.	.	.	.	.

Model Fit Statistics and Information Criteria
	log-likelihood	Deviance	AIC	BIC	AICc
.	.	.	.	.	.
.	.	.	.	.	.

Forest Plot

[3]


Test Name	value	p
.	.	.
.	.	.
.	.	.

Funnel Plot

[3]

Two One-Sided Tests Equivalence Testing
Z-Value Lower Bound	P-Value Lower Bound	Z-Value Upper Bound	P-Value Upper Bound	LL_CI_TOST	UL_CI_TOST	LL_CI_ZTEST	UL_CI_ZTEST
.	.	.	.	.	.	.	.

[0]

Two One-Sided Tests Equivalence Testing: Text Summary

Equivalence Test Plot

[0]

Outlier and Influential Case Diagnostics

Externally Standardized Residual

DFFITS Values

Cook's Distances

Covariance Ratios

Leave-one-out Tau Estimates

Leave-one-out (residual) Heterogeneity Test Statistics

Hat Values

Weights

Q-Q Plot

Meta-Analysis

This analysis has terminated, likely due to hitting a resource limit.

Random-Effects Model
	Estimate	se	Z	p	CI Lower Bound	CI Upper Bound
.	.	.	.	.	.	.
.	.	.	.	.	.	.

[3]

Heterogeneity Statistics
Tau	Tau²	I²	H²	R²	df	Q	p
.	.	.	.	.	.	.	.

Model Fit Statistics and Information Criteria
	log-likelihood	Deviance	AIC	BIC	AICc
.	.	.	.	.	.
.	.	.	.	.	.

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Selection Model Results
Estimate	SE	p-value	CI Lower Bound	CI Upper Bound
.	.	.	.	.

[3]


Test Name	value	p
.	.	.
.	.	.
.	.	.
.	.	.

Funnel Plot

[3]

Funnel Plot

[3]

Funnel Plot

[3]

Test of Excess Significance \| Significant Findings

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.		.
.		.

[0]

Test of Excess Significance \| Estimated Power of Tests
Min	Q1	Median	Q3	Max
.	.	.	.	.

[0]

p Curve Plot

Publication bias test p-uniform
Test Statistic		p-value
.		.

Effect size estimation p-uniform
Effect Size Estimate	CI Lower Bound	CI upper Bound	Z	p-value	Number of Significant Studies
.	.	.	.	.	.

Two One-Sided Tests Equivalence Testing
Z-Value Lower Bound	P-Value Lower Bound	Z-Value Upper Bound	P-Value Upper Bound	Lower Limit Confidence Interval TOST	Upper Limit Confidence Interval TOST	LL_CI_ZTEST	Z-Value Upper Limit Confidence Interval TOST
.	.	.	.	.	.	.	.

[0]

Equivalence Test Plot

[0]

Likelihood Plot

[0]

Outlier and Influential Case Diagnostics

Externally Standardized Residual

DFFITS Values

Cook's Distances

Covariance Ratios

Leave-one-out Tau Estimates

Leave-one-out (residual) Heterogeneity Test Statistics

Hat Values

Weights

Q-Q Plot

Meta-Analysis

This analysis has terminated, likely due to hitting a resource limit.

Random-Effects Model
	Estimate	se	Z	p	CI Lower Bound	CI Upper Bound
.	.	.	.	.	.	.
.	.	.	.	.	.	.

[3]

Heterogeneity Statistics
Tau	Tau²	I²	H²	R²	df	Q	p
.	.	.	.	.	.	.	.

Model Fit Statistics and Information Criteria
	log-likelihood	Deviance	AIC	BIC	AICc
.	.	.	.	.	.
.	.	.	.	.	.

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Selection Model Results
Estimate	SE	p-value	CI Lower Bound	CI Upper Bound
.	.	.	.	.

[3]


Test Name	value	p
.	.	.
.	.	.
.	.	.
.	.	.

Funnel Plot

[3]

Funnel Plot

[3]

Funnel Plot

[3]

Test of Excess Significance \| Significant Findings

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.		.

[0]

Test of Excess Significance \| Estimated Power of Tests
Min	Q1	Median	Q3	Max
.	.	.	.	.

[0]

p Curve Plot

Publication bias test p-uniform
Test Statistic		p-value
.		.

Effect size estimation p-uniform
Effect Size Estimate	CI Lower Bound	CI upper Bound	Z	p-value	Number of Significant Studies
.	.	.	.	.	.

Two One-Sided Tests Equivalence Testing
Z-Value Lower Bound	P-Value Lower Bound	Z-Value Upper Bound	P-Value Upper Bound	Lower Limit Confidence Interval TOST	Upper Limit Confidence Interval TOST	LL_CI_ZTEST	Z-Value Upper Limit Confidence Interval TOST
.	.	.	.	.	.	.	.

[0]

Equivalence Test Plot

[0]

Likelihood Plot

[0]

Outlier and Influential Case Diagnostics

Externally Standardized Residual

DFFITS Values

Cook's Distances

Covariance Ratios

Leave-one-out Tau Estimates

Leave-one-out (residual) Heterogeneity Test Statistics

Hat Values

Weights

Q-Q Plot

Meta-Analysis

Random-Effects Model (k = 13)
	Estimate	se	Z	p	CI Lower Bound	CI Upper Bound
Intercept	0.303	0.124	2.45	0.014	0.060	0.546
	.	.	.	.	.	.
Note. Tau² Estimator: Restricted Maximum-Likelihood

[3]

Heterogeneity Statistics
Tau	Tau²	I²	H²	R²	df	Q	p
0.315	0.0989 (SE= 0.0793 )	52.36%	2.099	.	12.000	25.475	0.013

The analysis was carried out using the standardized mean difference as the outcome measure. A random-effects model was fitted to the data. The amount of heterogeneity (i.e., tau²), was estimated using the restricted maximum-likelihood estimator (Viechtbauer 2005). In addition to the estimate of tau², the Q-test for heterogeneity (Cochran 1954) and the I² statistic are reported. In case any amount of heterogeneity is detected (i.e., tau² > 0, regardless of the results of the Q-test), a prediction interval for the true outcomes is also provided. Studentized residuals and Cook's distances are used to examine whether studies may be outliers and/or influential in the context of the model. Studies with a studentized residual larger than the 100 x (1 - 0.05/(2 X k))th percentile of a standard normal distribution are considered potential outliers (i.e., using a Bonferroni correction with two-sided alpha = 0.05 for k studies included in the meta-analysis). Studies with a Cook's distance larger than the median plus six times the interquartile range of the Cook's distances are considered to be influential. The rank correlation test and the regression test, using the standard error of the observed outcomes as predictor, are used to check for funnel plot asymmetry.

A total of k=13 studies were included in the analysis. The observed standardized mean differences ranged from -0.5950 to 0.9007, with the majority of estimates being positive (69%). The estimated average standardized mean difference based on the random-effects model was \hat{\mu} = 0.3033 (95% CI: 0.0605 to 0.5462). Therefore, the average outcome differed significantly from zero (z = 2.4481, p = 0.0144). According to the Q-test, the true outcomes appear to be heterogeneous (Q(12) = 25.4749, p = 0.0127, tau² = 0.0989, I² = 52.3638%). A 95% prediction interval for the true outcomes is given by -0.3591 to 0.9658. Hence, although the average outcome is estimated to be positive, in some studies the true outcome may in fact be negative. An examination of the studentized residuals revealed that none of the studies had a value larger than ± 2.8905 and hence there was no indication of outliers in the context of this model. According to the Cook's distances, none of the studies could be considered to be overly influential. Neither the rank correlation nor the regression test indicated any funnel plot asymmetry (p = 0.2044 and p = 0.0866, respectively).

Forest Plot

[3]

Publication Bias Assessment
Test Name	value	p
Fail-Safe N	46.000	< .001
Begg and Mazumdar Rank Correlation	-0.282	0.204
Egger's Regression	-1.714	0.087
Trim and Fill Number of Studies	0.000	.
Note. Fail-safe N Calculation Using the Rosenthal Approach

Funnel Plot

[3]

Meta-Analysis

This analysis has terminated, likely due to hitting a resource limit.

Random-Effects Model
	Estimate	se	Z	p	CI Lower Bound	CI Upper Bound
.	.	.	.	.	.	.
.	.	.	.	.	.	.

[3]

Heterogeneity Statistics
Tau	Tau²	I²	H²	R²	df	Q	p
.	.	.	.	.	.	.	.

Model Fit Statistics and Information Criteria
	log-likelihood	Deviance	AIC	BIC	AICc
.	.	.	.	.	.
.	.	.	.	.	.

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Forest Plot

[3]

Selection Model Results
Estimate	SE	p-value	CI Lower Bound	CI Upper Bound
.	.	.	.	.

[3]


Test Name	value	p
.	.	.
.	.	.
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.	.	.

Funnel Plot

[3]

Funnel Plot

[3]

Funnel Plot

[3]

Test of Excess Significance \| Significant Findings

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[4]

Test of Excess Significance \| Estimated Power of Tests
Min	Q1	Median	Q3	Max
.	.	.	.	.

[4]

p Curve Plot

Publication bias test p-uniform
Test Statistic		p-value
.		.

Effect size estimation p-uniform
Effect Size Estimate	CI Lower Bound	CI upper Bound	Z	p-value	Number of Significant Studies
.	.	.	.	.	.

Two One-Sided Tests Equivalence Testing
Z-Value Lower Bound	P-Value Lower Bound	Z-Value Upper Bound	P-Value Upper Bound	Lower Limit Confidence Interval TOST	Upper Limit Confidence Interval TOST	LL_CI_ZTEST	Z-Value Upper Limit Confidence Interval TOST
.	.	.	.	.	.	.	.

[5]

Equivalence Test Plot

[5]

Likelihood Plot

[6]

Outlier and Influential Case Diagnostics

Externally Standardized Residual

DFFITS Values

Cook's Distances

Covariance Ratios

Leave-one-out Tau Estimates

Leave-one-out (residual) Heterogeneity Test Statistics

Hat Values

Weights

Q-Q Plot

References

[1] The jamovi project (2021). jamovi. (Version 2.2) [Computer Software]. Retrieved from https://www.jamovi.org.

[2] R Core Team (2021). R: A Language and environment for statistical computing. (Version 4.0) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from MRAN snapshot 2021-04-01).

[3] Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software. link, 36, 1-48.