Aggregate data meta-analysis is currently the most commonly used method for combining the results from different studies on the same outcome of interest. In this paper, we provide a brief introduction to meta-analysis...Aggregate data meta-analysis is currently the most commonly used method for combining the results from different studies on the same outcome of interest. In this paper, we provide a brief introduction to meta-analysis, including a description of aggregate and individual participant data meta-analysis. We then focus the rest of the tutorial on aggregate data metaanalysis. We start by first describing the difference between fixed and random-effects meta-analysis, with particular attention devoted to the latter. This is followed by an example using the random-effects, method of moments approach and includes an intercept-only model as well as a model with one predictor. We then describe alternative random-effects approaches such as maximum likelihood, restricted maximum likelihood and profile likelihood as well as a non-parametric approach. A brief description of selected statistical programs available to conduct random-effects aggregate data meta-analysis, limited to those that allow both an interceptonly as well as at least one predictor in the model, is given. These descriptions include those found in an existing general statistics software package as well as one developed specifically for an aggregate data metaanalysis. Following this, some of the disadvantages of random-effects meta-analysis are described. We then describe recently proposed alternative models for conducting aggregate data meta-analysis, including the varying coefficient model. We conclude the paper with some recommendations and directions for future research. These recommendations include the continued use of the more commonly used random-effects models until newer models are more thoroughly tested as well as the timely integration of new and well-tested models into traditional as well as meta-analytic-specific software packages.展开更多
AIM: To determine whether evidential value exists that exercise reduces depression in adults with arthritis and other rheumatic conditions.METHODS: Utilizing data derived from a prior metaanalysis of 29 randomized con...AIM: To determine whether evidential value exists that exercise reduces depression in adults with arthritis and other rheumatic conditions.METHODS: Utilizing data derived from a prior metaanalysis of 29 randomized controlled trials comprising 2449 participants(1470 exercise, 979 control) with fibromyalgia, osteoarthritis, rheumatoid arthritis or systemic lupus erythematosus, a new method, P-curve, was utilized to assess for evidentiary worth as well as dismiss the possibility of discriminating reporting of statistically significant results regarding exercise and depression in adults with arthritis and other rheumatic conditions. Using the method of Stouffer, Z-scores were calculated to examine selective-reporting bias. An alpha(P) value < 0.05 was deemed statistically significant. In addition, average power of the tests included in P-curve, adjusted for publication bias, was calculated. RESULTS: Fifteen of 29 studies(51.7%) with exercise and depression results were statistically significant(P < 0.05) while none of the results were statistically significant with respect to exercise increasing depression in adults with arthritis and other rheumatic conditions. Right-skew to dismiss selective reporting was identified(Z =-5.28, P < 0.0001). In addition, the included studies did not lack evidential value(Z = 2.39, P = 0.99), nor did they lack evidential value and were P-hacked(Z = 5.28, P > 0.99). The relative frequencies of P-values were 66.7% at 0.01, 6.7% each at 0.02 and 0.03, 13.3% at 0.04 and 6.7% at 0.05. The average power ofthe tests included in P-curve, corrected for publication bias, was 69%. Diagnostic plot results revealed that the observed power estimate was a better fit than the alternatives. CONCLUSION: Evidential value results provide additiona support that exercise reduces depression in adults with arthritis and other rheumatic conditions.展开更多
AIM: Use a recently developed varying coefficient model to determine the effects of exercise in adults with depression.METHODS: Data from a recent meta-analysis addressing the effects of exercise on depression in adul...AIM: Use a recently developed varying coefficient model to determine the effects of exercise in adults with depression.METHODS: Data from a recent meta-analysis addressing the effects of exercise on depression in adults were used. Studies were limited to randomized controlled intervention trials of any type of chronic exercise(for example, walking and jogging) in adults greater than or equal to 18 years of age with a diagnosis of depression. For each study, the standardized mean difference(exercise minus control) effect size for depression, adjusted for small-sample bias, was calculated. Variance statistics for each effect size and pooling of results were calculated using the recently proposed varying coefficient(VC) model for standardized mean differences. Standardized effect-sizes of 0.20, 0.50 and 0.80 were considered to represent small, medium and large effects. Results were considered statistically significant if the 95% confidence intervals did not cross 0, with negative results indicative of reductions in depression.These findings were then compared with results using traditional random-effects(RE) models.RESULTS: A total of 23 studies representing 907 men and women(476 exercise, 431 control) were pooled for analysis. Both RE and VC models resulted in large, statistically significant improvements in depression as a result of exercise in adults. However, the VC model resulted in a larger overall effect size as well as confidence intervals that were narrower than previously reported using the RE model. The overall mean effect size for the RE model was-0.82 with a 95% confidence interval of-1.12 to-0.51. For the VC model, overall mean effect size was-0.88 with a 95% confidence interval of-1.08 to-0.68. The relative difference between the RE and VC approaches was 7.3%.CONCLUSION: The VC model, a potentially preferable model, confirms the positive effects of exercise on depression in adults.展开更多
基金Supported by Grant R01 HL069802 from the National Institutes of Health,National Heart,Lung and Blood Institute(to Kelley GA)
文摘Aggregate data meta-analysis is currently the most commonly used method for combining the results from different studies on the same outcome of interest. In this paper, we provide a brief introduction to meta-analysis, including a description of aggregate and individual participant data meta-analysis. We then focus the rest of the tutorial on aggregate data metaanalysis. We start by first describing the difference between fixed and random-effects meta-analysis, with particular attention devoted to the latter. This is followed by an example using the random-effects, method of moments approach and includes an intercept-only model as well as a model with one predictor. We then describe alternative random-effects approaches such as maximum likelihood, restricted maximum likelihood and profile likelihood as well as a non-parametric approach. A brief description of selected statistical programs available to conduct random-effects aggregate data meta-analysis, limited to those that allow both an interceptonly as well as at least one predictor in the model, is given. These descriptions include those found in an existing general statistics software package as well as one developed specifically for an aggregate data metaanalysis. Following this, some of the disadvantages of random-effects meta-analysis are described. We then describe recently proposed alternative models for conducting aggregate data meta-analysis, including the varying coefficient model. We conclude the paper with some recommendations and directions for future research. These recommendations include the continued use of the more commonly used random-effects models until newer models are more thoroughly tested as well as the timely integration of new and well-tested models into traditional as well as meta-analytic-specific software packages.
基金Supported by The National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health(GAK,Principal Investigator),No.RO1AR061346the National Institute of General Medical Sciences of the National Institutes of Health,No.U54GM104942
文摘AIM: To determine whether evidential value exists that exercise reduces depression in adults with arthritis and other rheumatic conditions.METHODS: Utilizing data derived from a prior metaanalysis of 29 randomized controlled trials comprising 2449 participants(1470 exercise, 979 control) with fibromyalgia, osteoarthritis, rheumatoid arthritis or systemic lupus erythematosus, a new method, P-curve, was utilized to assess for evidentiary worth as well as dismiss the possibility of discriminating reporting of statistically significant results regarding exercise and depression in adults with arthritis and other rheumatic conditions. Using the method of Stouffer, Z-scores were calculated to examine selective-reporting bias. An alpha(P) value < 0.05 was deemed statistically significant. In addition, average power of the tests included in P-curve, adjusted for publication bias, was calculated. RESULTS: Fifteen of 29 studies(51.7%) with exercise and depression results were statistically significant(P < 0.05) while none of the results were statistically significant with respect to exercise increasing depression in adults with arthritis and other rheumatic conditions. Right-skew to dismiss selective reporting was identified(Z =-5.28, P < 0.0001). In addition, the included studies did not lack evidential value(Z = 2.39, P = 0.99), nor did they lack evidential value and were P-hacked(Z = 5.28, P > 0.99). The relative frequencies of P-values were 66.7% at 0.01, 6.7% each at 0.02 and 0.03, 13.3% at 0.04 and 6.7% at 0.05. The average power ofthe tests included in P-curve, corrected for publication bias, was 69%. Diagnostic plot results revealed that the observed power estimate was a better fit than the alternatives. CONCLUSION: Evidential value results provide additiona support that exercise reduces depression in adults with arthritis and other rheumatic conditions.
文摘AIM: Use a recently developed varying coefficient model to determine the effects of exercise in adults with depression.METHODS: Data from a recent meta-analysis addressing the effects of exercise on depression in adults were used. Studies were limited to randomized controlled intervention trials of any type of chronic exercise(for example, walking and jogging) in adults greater than or equal to 18 years of age with a diagnosis of depression. For each study, the standardized mean difference(exercise minus control) effect size for depression, adjusted for small-sample bias, was calculated. Variance statistics for each effect size and pooling of results were calculated using the recently proposed varying coefficient(VC) model for standardized mean differences. Standardized effect-sizes of 0.20, 0.50 and 0.80 were considered to represent small, medium and large effects. Results were considered statistically significant if the 95% confidence intervals did not cross 0, with negative results indicative of reductions in depression.These findings were then compared with results using traditional random-effects(RE) models.RESULTS: A total of 23 studies representing 907 men and women(476 exercise, 431 control) were pooled for analysis. Both RE and VC models resulted in large, statistically significant improvements in depression as a result of exercise in adults. However, the VC model resulted in a larger overall effect size as well as confidence intervals that were narrower than previously reported using the RE model. The overall mean effect size for the RE model was-0.82 with a 95% confidence interval of-1.12 to-0.51. For the VC model, overall mean effect size was-0.88 with a 95% confidence interval of-1.08 to-0.68. The relative difference between the RE and VC approaches was 7.3%.CONCLUSION: The VC model, a potentially preferable model, confirms the positive effects of exercise on depression in adults.
