Positive estimation of the between-group variance component in one-way anova and meta-analysis

Positive estimators of the between-group (between-study) variance are proposed. Explicit variance formulae for the estimators are given and approximate confidence intervals for the between-group variance are constructed, as our proposal to a long outstanding problem. By Monte Carlo simulation, the bias and standard deviation of the proposed estimators are compared with the truncated versions of the maximum likelihood (ML) estimator, restricted maximum likelihood (REML) estimator and a (lately) standard estimator in meta-analysis. Attained confidence coefficients of the constructed confidence intervals are also presented

Alternative Test Procedures and Confidence Intervals on the Common Mean in the Fixed Effects Model for Meta-Analysis

The best linear unbiased estimator of the common mean in heteroscedastic one-way fixed effects model exists only if the values of the variance components are known. In practice this does not hold and so far there exists no consensus on the most suitable test for the common mean parameter. With respect to the attained significance levels, the

A Joint assessment of outcomes in quantitative evidence synthesis

Paper presented at the 4th Strathmore International Mathematics Conference (SIMC 2017), 19 - 23 June 2017, Strathmore University, Nairobi, Kenya.Quantitative research synthesis (or meta-analysis) has seen significant methodological development in the application of multivariate methods for the comparison of multiple endpoints. Multivariate meta-analysis offers some advantages over separate univariate analyses including the ability to borrow strength across studies and outcomes. The issue of heterogeneity among studies is very important in meta- analysis and partly entails the estimation of the heterogeneity variance. A number of iterative and non-iterative estimators for the heterogeneity variance have been proposed with no clear consensus on the best estimator with respect to selected performance indices. We present an overview of the univariate random effects meta- analytic approach including an example on application in randomized clinical trials. A multivariate alternative to the extended DerSimonian-Laird (DL) method (the commonly used method) will be presented. A comparison of the bias and mean square error from a simulation study indicates that, in some circumstances, the proposed method performs better than the multivariate DL method. Other topics of interest in multivariate meta-analysis will be discussed including network meta- analysis and integrating meta-analysis into structural equation models (SEM) that can be implemented in the mainstream SEM software including MPLUS.Georgetown University, Washington, DC 20057, US

Racial Differences in the Impact of Adolescent Depression on Families in TADS

This manuscript examines racial differences in the impact of adolescent depression between White, African American, and Latino families. Findings are from the Treatment for Adolescents with Depression Study (TADS), a multi-site clinical research study evaluating the efficacy of CBT and Fluoxetine for treating adolescents with major depressive disorder. Primary caretakers of 439 adolescents with depression were interviewed. Results demonstrated that compared to White families, African American and Latino families were more likely to report increased feelings of tiredness or anergia (p\u3c.05) and more physical health problems (p\u3c.01) associated with caring for a depressed teen. The conclusion suggests the need for a better understanding of depression in people and families of color and offers recommendations for further research

Use of multivitamins, folic acid and herbal supplements among breast cancer survivors: the black women's health study

<p>Abstract</p> <p>Background</p> <p>Complementary and alternative medicine (CAM) use, including herbals and multivitamin supplements, is quite common in the U.S., and has been shown to be highest in breast cancer survivors. However, limited data are currently available for CAM usage among African Americans. Thus, we sought to determine the prevalence of multivitamins, folic acid and herbal supplement usage in African American breast cancer survivors, and to compare the characteristics of users and nonusers.</p> <p>Methods</p> <p>A cohort study of breast cancer survivors, who completed the 1999 Black Women's Health Study questionnaire and self-reported having been diagnosed with breast cancer between 1995 and 1999, comprised the study population. In this study, the intake of natural herbs, multivitamins and folic acid at least three days per week within the past two years was used as a proxy for typical usage of this complimentary alternative medicine (CAM) modality.</p> <p>Results</p> <p>A total of 998 breast cancer survivors were identified. Overall, 68.2% had used either herbals or multivitamin supplements or both. The three most frequently used herbals were garlic (21.2%), gingko (12.0%), and echinacea (9.4%). The multivariate analysis determined that single marital status (OR = 1.58; 95%CI: 1.04-2.41), and alcohol consumption of 1-3 drinks per week (OR = 1.86, 95%CI: 1.28-2.68) were significantly associated with increased herbal use. Multivitamin use was significantly lower among obese women (OR = 0.66, 95%CI: 0.46-0.94) and current smokers (OR = 0.53, 95%CI: 0.34-0.82).</p> <p>Conclusions</p> <p>A significant number of African American breast cancer survivors are using herbals and multivitamins as CAM modality. Additional research is needed to understand the impact of herbals and multivitamins in African American breast cancer survivors.</p

MicroRNA-9 as Potential Biomarker for Breast Cancer Local Recurrence and Tumor Estrogen Receptor Status

MicroRNAs (miRs) are small, non-protein coding transcripts involved in many cellular functions. Many miRs have emerged as important cancer biomarkers. In the present study, we investigated whether miR levels in breast tumors are predictive of breast cancer local recurrence (LR). Sixty-eight women who were diagnosed with breast cancer at the Lombardi Comprehensive Cancer Center were included in this study. Breast cancer patients with LR and those without LR were matched on year of surgery, age at diagnosis, and type of surgery. Candidate miRs were identified by screening the expression levels of 754 human miRs using miR arrays in 16 breast tumor samples from 8 cases with LR and 8 cases without LR. Eight candidate miRs that showed significant differences between tumors with and without LR were further verified in 52 tumor samples using real-time PCR. Higher expression of miR-9 was significantly associated with breast cancer LR in all cases as well as the subset of estrogen receptor (ER) positive cases (p = 0.02). The AUCs (Area Under Curve) of receiver operating characteristic (ROC) curves of miR-9 for all tumors and ER positive tumors are 0.68 (p = 0.02) and 0.69 (p = 0.02), respectively. In ER positive cases, Kaplan-Meier analysis showed that patients with lower miR-9 levels had significantly better 10-year LR-free survival (67.9% vs 30.8%, p = 0.02). Expression levels of miR-9 and another miR candidate, miR-375, were also strongly associated with ER status (p<0.001 for both). The potential of miR-9 as a biomarker for LR warrants further investigation with larger sample size

The effect of the heterogeneity variance estimator on some tests of treatment efficacy

The effect of two noniterative heterogeneity variance estimators on two test procedures for the overall treatment effect using the log odds ratio as the outcome measure is investigated. Using simulated significance levels, it is shown that in addition to being sensitive to changes in the magnitude of the heterogeneity variance, the standard test procedure in meta-analysis (or multicenter clinical trials) is also sensitive to the heterogeneity variance estimator used and attains significance levels that are far from the prescribed level. A second test procedure by Hartung [Hartung, J. (1999). An alternative method for meta-analysis. Biometrical J. 41:901-916], is shown to exhibit good control of type I error probability regardless of changes in the magnitude of the heterogeneity variance and the heterogeneity variance estimator used

Weighted inverse chi-square method for correlated significance tests

Fisher\u27s inverse chi-square method for combining independent significance tests is extended to cover cases of dependence among the individual tests. A weighted version of the method and its approximate null distribution are presented. To illustrate the use of the proposed method, two tests for the overall treatment efficacy are combined, with the resulting test procedure exhibiting good control of the type I error probability. Two examples from clinical trials are given to illustrate the applicability of the procedures to real-life situations