Amita K Manatunga

Emory University, Atlanta, Georgia, United States

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Publications (106)426.74 Total impact

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    ABSTRACT: Pooling specimens prior to performing laboratory assays has various benefits. Pooling can help to reduce cost, preserve irreplaceable specimens, meet minimal volume requirements for certain lab tests, and even reduce information loss when a limit of detection is present. Regardless of the motivation for pooling, appropriate analytical techniques must be applied in order to obtain valid inference from composite specimens. When biomarkers are treated as the outcome in a regression model, techniques applicable to individually measured specimens may not be valid when measurements are taken from pooled specimens, particularly when the biomarker is positive and right skewed. In this paper, we propose a novel semiparametric estimation method based on an adaptation of the quasi-likelihood approach that can be applied to a right-skewed outcome subject to pooling. We use simulation studies to compare this method with an existing estimation technique that provides valid estimates only when pools are formed from specimens with identical predictor values. Simulation results and analysis of a motivating example demonstrate that, when appropriate estimation techniques are applied to strategically formed pools, valid and efficient estimation of the regression coefficients can be achieved. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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    ABSTRACT: The role of endothelium-derived hyperpolarizing factor (EDHF) in either the healthy circulation or in those with hypercholesterolemia is unknown. In healthy and hypercholesterolemic subjects, we measured forearm blood flow (FBF) using strain-gauge plethysmography at rest, during graded handgrip exercise, and after sodium nitroprusside infusion. Measurements were repeated after l-NMMA, tetraethylammonium (TEA), and combined infusions. At rest, l-NMMA infusion reduced FBF in healthy but not hypercholesterolemic subjects. At peak exercise, vasodilation was lower in hypercholesterolemic compared to healthy subjects (274% vs 438% increase in FBF, p=0.017). TEA infusion reduced exercise-induced vasodilation in both healthy and hypercholesterolemic subjects (27%, p<0.0001 and -20%, p<0.0001, respectively). The addition of l-NMMA to TEA further reduced FBF in healthy (-14%, p=0.012) but not in hypercholesterolemic subjects, indicating a reduced nitric oxide and greater EDHF-mediated contribution to exercise-induced vasodilation in hypercholesterolemia. In conclusion, exercise-induced vasodilation is impaired and predominantly mediated by EDHF in hypercholesterolemic subjects. Clinical Trial Registration Identifier: NCT00166166. © The Author(s) 2015.
    Vascular Medicine 02/2015; DOI:10.1177/1358863X14565374 · 1.73 Impact Factor
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    ABSTRACT: The potential for research involving biospecimens can be hindered by the prohibitive cost of performing laboratory assays on individual samples. To mitigate this cost, strategies such as randomly selecting a portion of specimens for analysis or randomly pooling specimens prior to performing laboratory assays may be employed. These techniques, while effective in reducing cost, are often accompanied by a considerable loss of statistical efficiency. We propose a novel pooling strategy based on the k-means clustering algorithm to reduce laboratory costs while maintaining a high level of statistical efficiency when predictor variables are measured on all subjects, but the outcome of interest is assessed in pools. We perform simulations motivated by the BioCycle study to compare this k-means pooling strategy with current pooling and selection techniques under simple and multiple linear regression models. While all of the methods considered produce unbiased estimates and confidence intervals with appropriate coverage, pooling under k-means clustering provides the most precise estimates, closely approximating results from the full data and losing minimal precision as the total number of pools decreases. The benefits of k-means clustering evident in the simulation study are then applied to an analysis of the BioCycle dataset. In conclusion, when the number of lab tests is limited by budget, pooling specimens based on k-means clustering prior to performing lab assays can be an effective way to save money with minimal information loss in a regression setting. Copyright © 2014 John Wiley & Sons, Ltd.
    Statistics in Medicine 09/2014; DOI:10.1002/sim.6305 · 2.04 Impact Factor
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    ABSTRACT: Aims: Bradykinin (BK) stimulates tissue plasminogen activator (t-PA) release from human endothelium. Although BK stimulates both nitric oxide and endothelium-derived hyperpolarizing factor (EDHF) release, the role of EDHF in t-PA release remains unexplored. This study sought to determine the mechanisms of BK-stimulated t-PA release in the forearm vasculature of healthy human subjects. Methods: In 33 healthy subjects (age 40.3 ± 1.9 years), forearm blood flow (FBF) and t-PA release were measured at rest and after intra-arterial infusions of BK (400 ng/min) and sodium nitroprusside (3.2 mg/min). Measurements were repeated after intra-arterial infusion of tetraethylammonium chloride (TEA; 1 µmol/min), fluconazole (0.4 µmol·min(-1)·l(-1)), and N(G)-monomethyl-L-arginine (L-NMMA, 8 µmol/min) to block nitric oxide, and their combination in separate studies. Results: BK significantly increased net t-PA release across the forearm (p < 0.0001). Fluconazole attenuated both BK-mediated vasodilation (-23.3 ± 2.7% FBF, p < 0.0001) and t-PA release (from 50.9 ± 9.0 to 21.3 ± 8.9 ng/min/100 ml, p = 0.02). TEA attenuated FBF (-14.7 ± 3.2%, p = 0.002) and abolished BK-stimulated t-PA release (from 22.9 ± 5.7 to -0.8 ± 3.6 ng/min/100 ml, p = 0.0002). L-NMMA attenuated FBF (p < 0.0001), but did not inhibit BK-induced t-PA release (nonsignificant). Conclusion: BK-stimulated t-PA release is partly due to cytochrome P450-derived epoxides and is inhibited by K(+)Ca channel blockade. Thus, BK stimulates both EDHF-dependent vasodilation and t-PA release. © 2014 S. Karger AG, Basel.
    Journal of Vascular Research 06/2014; 51(3):200-208. DOI:10.1159/000362666 · 2.44 Impact Factor
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    ABSTRACT: Abnormalities in nitric oxide (NO) bioavailability have been reported in blacks. Whether there are differences in endothelium-derived hyperpolarizing factor (EDHF) in addition to NO between blacks and whites and how these affect physiological vasodilation remain unknown. We hypothesized that the bioavailability of vascular NO and EDHF, at rest and with pharmacological and physiological vasodilation, varies between whites and blacks. In 74 white and 86 black subjects without known cardiovascular disease risk factors, forearm blood flow was measured using plethysmography at rest and during inhibition of NO with N(G)-monomethyl-l-arginine and of K(+)Ca channels (EDHF) with tetraethylammonium. The reduction in resting forearm blood flow was greater with N(G)-monomethyl-l-arginine (P=0.019) and similar with tetraethylammonium in whites compared with blacks. Vasodilation with bradykinin, acetylcholine, and sodium nitroprusside was lower in blacks compared with whites (all P<0.0001). Inhibition with N(G)-monomethyl-l-arginine was greater in whites compared with blacks with bradykinin, acetylcholine, and exercise. Inhibition with tetraethylammonium was lower in blacks with bradykinin, but greater during exercise and with acetylcholine. The contribution to both resting and stimulus-mediated vasodilator tone of NO is greater in whites compared with blacks. EDHF partly compensates for the reduced NO release in exercise and acetylcholine-mediated vasodilation in blacks. Preserved EDHF but reduced NO bioavailability and sensitivity characterizes the vasculature in healthy blacks. http://clinicaltrials.gov/. Unique identifier: NCT00166166.
    Arteriosclerosis Thrombosis and Vascular Biology 03/2014; 34(6). DOI:10.1161/ATVBAHA.113.303136 · 6.34 Impact Factor
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    ABSTRACT: Epidemiological studies involving biomarkers are often hindered by prohibitively expensive laboratory tests. Strategically pooling specimens prior to performing these lab assays has been shown to effectively reduce cost with minimal information loss in a logistic regression setting. When the goal is to perform regression with a continuous biomarker as the outcome, regression analysis of pooled specimens may not be straightforward, particularly if the outcome is right-skewed. In such cases, we demonstrate that a slight modification of a standard multiple linear regression model for poolwise data can provide valid and precise coefficient estimates when pools are formed by combining biospecimens from subjects with identical covariate values. When these x-homogeneous pools cannot be formed, we propose a Monte Carlo expectation maximization (MCEM) algorithm to compute maximum likelihood estimates (MLEs). Simulation studies demonstrate that these analytical methods provide essentially unbiased estimates of coefficient parameters as well as their standard errors when appropriate assumptions are met. Furthermore, we show how one can utilize the fully observed covariate data to inform the pooling strategy, yielding a high level of statistical efficiency at a fraction of the total lab cost.
    Biometrics 02/2014; DOI:10.1111/biom.12134 · 1.52 Impact Factor
  • Ying Guo, Ruosha Li, Limin Peng, Amita K Manatunga
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    ABSTRACT: The need to assess agreement arises in many scenarios in biomedical sciences when measurements were taken by different methods on the same subjects. When the endpoints are survival outcomes, the study of agreement becomes more challenging given the special characteristics of time-to-event data. In this article, we propose a new framework for assessing agreement based on survival processes that can be viewed as a natural representation of time-to-event outcomes. Our new agreement measure is formulated as the chance-corrected concordance between survival processes. It provides a new perspective for studying the relationship between correlated survival outcomes and offers an appealing interpretation as the agreement between survival times on the absolute distance scale. We provide a multivariate extension of the proposed agreement measure for multiple methods. Furthermore, the new framework enables a natural extension to evaluate time-dependent agreement structure. We develop nonparametric estimation of the proposed new agreement measures. Our estimators are shown to be strongly consistent and asymptotically normal. We evaluate the performance of the proposed estimators through simulation studies and then illustrate the methods using a prostate cancer data example.
    Biometrics 07/2013; 69(4):1-9. DOI:10.1111/biom.12063 · 1.52 Impact Factor
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    ABSTRACT: PURPOSE: The purposes of this study were to establish reference values for renal size determined from Tc-MAG3 renal scintigraphy and to derive regression equations to predict normal limits. METHODS: The study population consisted of 106 subjects evaluated for kidney donation who underwent Tc-MAG3 renal scintigraphy. Renal length, width, and area were determined from the pixel length and area of whole-kidney regions of interest and correlated with patient sex, height, weight, body mass index, and body surface area (BSA). Reference values were obtained based on estimation of the lower and upper percentiles via quantile regression. RESULTS: The mean (SD) left and right kidney lengths was 12.2 (1.0) and 12.1 (1.0) in male and 11.9 (0.9) and 11.8 (0.9) in female patients, respectively. Sex was not a significant factor in the quantile regression models. Regression equations defining the lower and upper limits of renal length (cm) and area (cm) are as follows: left kidney length (5th percentile), 8.2 + 1.3 × BSA; left kidney length (95th percentile), 9.1 + 2.3 × BSA; right kidney length (5th percentile), 8.8 + 1.0 × BSA; right kidney length (95th percentile), 11.1 + 1.4 × BSA; left kidney area (5th percentile), 32.5 + 9.6 × BSA; left kidney area (95th percentile), 12.6 + 31.7 × BSA; right kidney area (5th percentile), 16.1 + 18.5 × BSA; right kidney area (95th percentile), 32.6 + 22.2 × BSA. CONCLUSIONS: Regression equations have been developed, which define the upper and lower limits of renal size from Tc-MAG3 images and may assist in the detection of unsuspected bilateral increases or decreases in renal size.
    Clinical nuclear medicine 12/2012; 38(1). DOI:10.1097/RLU.0b013e318270866f · 3.92 Impact Factor
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    ABSTRACT: Objective. As few, small studies have examined the impact of electroconvulsive therapy (ECT) upon the heart rate variability of patients with major depressive disorder (MDD), we sought to confirm whether ECT-associated improvement in depressive symptoms would be associated with increases in HRV linear and nonlinear parameters. Methods. After providing consent, depressed study participants (n = 21) completed the Beck Depression Index (BDI), and 15-minute Holter monitor recordings, prior to their 1st and 6th ECT treatments. Holter recordings were analyzed for certain HRV indices: root mean square of successive differences (RMSSD), low-frequency component (LF)/high-frequency component (HF) and short-(SD1) versus long-term (SD2) HRV ratios. Results. There were no significant differences in the HRV indices of RMSDD, LF/HF, and SD1/SD2 between the patients who responded, and those who did not, to ECT. Conclusion. In the short term, there appear to be no significant improvement in HRV in ECT-treated patients whose depressive symptoms respond versus those who do not. Future studies will reveal whether diminished depressive symptoms with ECT are reliably associated with improved sympathetic/parasympathetic balance over the long-term, and whether acute changes in sympathetic/parasympathetic balance predict improved mental- and cardiac-related outcomes.
    Cardiovascular Psychiatry and Neurology 08/2012; 2012:794043. DOI:10.1155/2012/794043
    This article is viewable in ResearchGate's enriched format
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    ABSTRACT: In patients at high risk for recurrence of malignant melanoma, interferon-α (IFN-α), a stimulator of innate immunity, appears to induce distinct neurobehavioral symptom dimensions: a mood and anxiety syndrome, and a neurovegetative syndrome, of which the former is responsive to prophylactic administration of paroxetine. We sought to determine whether symptom dimensions (and treatment responsiveness) arise in patients with hepatitis C administered IFN-α and ribavirin. In a randomized, double-blind, 6-month study, 61 patients with hepatitis C eligible for therapy with IFN-α and ribavirin received the antidepressant paroxetine (n=28) or a placebo (n=33). Study medication began 2 weeks before IFN-α/ribavirin therapy. Neuropsychiatric assessments included the 10-item Montgomery-Asberg Depression Rating Scale (MADRS). The items of the MADRS were grouped into depression, anxiety, cognitive dysfunction, and neurovegetative symptom dimensions, and analyzed using a mixed model. By 2 weeks of IFN-α/ribavirin therapy, all four dimensions increased, with the symptom dimensions of anxiety and cognitive dysfunction fluctuating and worsening, respectively, in both groups over time. The depression symptom dimension was significantly lower in the paroxetine treatment group (p=0.04); severity of the neurovegetative symptom dimension was similar in both groups. Similar to patients with malignant melanoma receiving high-dose IFN-α, the depression symptom dimension is more responsive to paroxetine treatment in individuals undergoing concomitant IFN-α/ribavirin therapy. However, the anxiety, cognitive dysfunction, and neurovegetative symptom dimensions appear less responsive to prophylactic paroxetine administration. Different neurobiologic pathways may contribute to the responsiveness of IFN-α-induced symptom dimensions to antidepressant treatment, requiring relevant psychopharmacologic strategies.
    Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology 02/2012; 37(6):1444-54. DOI:10.1038/npp.2011.330 · 8.68 Impact Factor
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    ABSTRACT: Nuclear magnetic resonance (NMR) spectroscopy, traditionally used in analytical chemistry, has recently been introduced to studies of metabolite composition of biological fluids and tissues. Metabolite levels change over time, and providing a tool for better extraction of NMR peaks exhibiting periodic behavior is of interest. We propose a method in which NMR peaks are clustered based on periodic behavior. Periodic regression is used to obtain estimates of the parameter corresponding to period for individual NMR peaks. A mixture model is then used to develop clusters of peaks, taking into account the variability of the regression parameter estimates. Methods are applied to NMR data collected from human blood plasma over a 24-hour period. Simulation studies show that the extra variance component due to the estimation of the parameter estimate should be accounted for in the clustering procedure.
    Statistical Analysis and Data Mining 12/2011; 4(6):579-589. DOI:10.1002/sam.10137
  • Limin Peng, Ruosha Li, Ying Guo, Amita Manatunga
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    ABSTRACT: Conventional agreement studies have been confined to addressing the sense of reproducibility, and therefore are limited to assessing measurements on the same scale. In this work, we propose a new concept, called "broad sense agreement," which extends the classical framework of agreement to evaluate the capability of interpreting a continuous measurement in an ordinal scale. We present a natural measure for broad sense agreement. Nonparametric estimation and inference procedures are developed for the proposed measure along with theoretical justifications. We also consider longitudinal settings which involve agreement assessments at multiple time points. Simulation studies have demonstrated good performance of the proposed method with small sample sizes. We illustrate our methods via an application to a mental health study.
    Journal of the American Statistical Association 12/2011; 106(496):1592-1601. DOI:10.1198/jasa.2011.tm10483 · 2.11 Impact Factor
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    ABSTRACT: The purpose of this study was to facilitate interpretation of (99m)Tc-mercaptoacetyltriglycine (MAG3) diuretic scans by identifying key interpretative variables and developing a predictive model for computer-assisted diagnosis. Ninety-seven studies were randomly selected from an archived database of MAG3 baseline and furosemide acquisitions and scan interpretations (obstruction, equivocal finding, or no obstruction) derived from a consensus of three experts. Sixty-one studies (120 kidneys) were randomly chosen to build a predictive model for diagnosing or excluding obstruction. The other 36 studies (71 kidneys) composed the validation group. The probability of normal drainage (no obstruction) at the baseline acquisition and the probability of no obstruction, equivocal finding, or obstruction after furosemide administration were determined by logistic regression analysis and proportional odds modeling of MAG3 renographic data. The single most important baseline variable for excluding obstruction was the ratio of postvoid counts to maximum counts. Renal counts in the last minute of furosemide acquisition divided by the maximum baseline acquisition renal counts and time to half-maximum counts after furosemide administration in a pelvic region of interest were the critical variables for determining obstruction. The area under the receiver operating characteristic curve (AUC) for predicting normal drainage in the validation sample was 0.93 (standard error, 0.02); sensitivity, 85%; specificity, 93%. The AUC for the diagnosis of obstruction after furosemide administration was 0.84 (standard error, 0.06); sensitivity, 82%; specificity, 83%. A predictive system has been developed that provides a promising computer-assisted diagnosis approach to the interpretation of MAG3 diuretic renal scans; this system has also identified the key variables required for scan interpretation.
    American Journal of Roentgenology 08/2011; 197(2):325-33. DOI:10.2214/AJR.10.5909 · 2.74 Impact Factor
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    ABSTRACT: Background The accuracy of computer-aided diagnosis (CAD) software is best evaluated by comparison to a gold standard which represents the true status of disease. In many settings, however, knowledge of the true status of disease is not possible and accuracy is evaluated against the interpretations of an expert panel. Common statistical approaches to evaluate accuracy include receiver operating characteristic (ROC) and kappa analysis but both of these methods have significant limitations and cannot answer the question of equivalence: Is the CAD performance equivalent to that of an expert? The goal of this study is to show the strength of log-linear analysis over standard ROC and kappa statistics in evaluating the accuracy of computer-aided diagnosis of renal obstruction compared to the diagnosis provided by expert readers. Methods Log-linear modeling was utilized to analyze a previously published database that used ROC and kappa statistics to compare diuresis renography scan interpretations (non-obstructed, equivocal, or obstructed) generated by a renal expert system (RENEX) in 185 kidneys (95 patients) with the independent and consensus scan interpretations of three experts who were blinded to clinical information and prospectively and independently graded each kidney as obstructed, equivocal, or non-obstructed. Results Log-linear modeling showed that RENEX and the expert consensus had beyond-chance agreement in both non-obstructed and obstructed readings (both p < 0.0001). Moreover, pairwise agreement between experts and pairwise agreement between each expert and RENEX were not significantly different (p = 0.41, 0.95, 0.81 for the non-obstructed, equivocal, and obstructed categories, respectively). Similarly, the three-way agreement of the three experts and three-way agreement of two experts and RENEX was not significantly different for non-obstructed (p = 0.79) and obstructed (p = 0.49) categories. Conclusion Log-linear modeling showed that RENEX was equivalent to any expert in rating kidneys, particularly in the obstructed and non-obstructed categories. This conclusion, which could not be derived from the original ROC and kappa analysis, emphasizes and illustrates the role and importance of log-linear modeling in the absence of a gold standard. The log-linear analysis also provides additional evidence that RENEX has the potential to assist in the interpretation of diuresis renography studies.
    06/2011; 1(5):1-8. DOI:10.1186/2191-219X-1-5
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    ABSTRACT: We assessed the contribution of endothelium-derived hyperpolarizing factors to resting and agonist-stimulated vasodilator tone in health and disease. Tetraethylammonium chloride (TEA) was used to inhibit K(+)(Ca) channel activation and fluconazole was used to inhibit cytochrome P450 2C9-mediated epoxyeicosatrienoic acid synthesis. We hypothesized that endothelium-derived hyperpolarizing factors contribute to resting vascular tone by K(+)(Ca) channel activation and epoxyeicosatrienoic acid release and that endothelium-derived hyperpolarizing factors compensate for reduced nitric oxide bioavailability at rest and with endothelium-dependent vasodilators. In 103 healthy subjects and 71 nonhypertensive subjects with multiple risk factors, we measured resting forearm blood flow (FBF) using venous occlusion plethysmography before and after intra-arterial infusions of N(G)-monomethyl-l-arginine (L-NMMA), TEA, fluconazole, and their combination. The effects of these antagonists on resting FBF and on bradykinin- and acetylcholine-mediated vasodilation were studied. Resting FBF decreased with TEA and L-NMMA in all subjects (P<0.001); however, the vasoconstrictor response to L-NMMA was greater (P=0.04) and to TEA was lower (P=0.04) in healthy subjects compared with those with risk factors. Fluconazole decreased resting FBF in all subjects, and the addition of TEA further reduced FBF after fluconazole, suggesting that cytochrome P450 metabolites and other hyperpolarizing factor(s) activate K(+)(Ca) channels. Both L-NMMA and TEA attenuated bradykinin-mediated vasodilation in healthy and hypercholesterolemic subjects (P<0.001). In contrast, acetylcholine-mediated vasodilation remained unchanged with TEA in healthy subjects but was significantly attenuated in hypercholesterolemia (P<0.04). First, by activating TEA-inhibitable K(+)(Ca) channels, endothelium-derived hyperpolarizing factors, together with nitric oxide, contribute to resting microvascular dilator tone. The contribution of K(+)(Ca) channel activation compared with nitric oxide is greater in those with multiple risk factors compared with healthy subjects. Second, activation of K(+)(Ca) channels is only partly through epoxyeicosatrienoic acid release, indicating the presence of other hyperpolarizing mechanisms. Third, bradykinin, but not acetylcholine, stimulates K(+)(Ca) channel-mediated vasodilation in healthy subjects, whereas in hypercholesterolemia, K(+)(Ca) channel-mediated vasodilation compensates for the reduced nitric oxide activity. Thus, enhanced endothelium-derived hyperpolarizing factor activity in conditions of nitric oxide deficiency contributes to maintenance of resting and agonist-stimulated vasodilation. Clinical Trial Registration- URL: http://www.clinicaltrials.gov. Unique identifier: NCT00166166.
    Circulation 05/2011; 123(20):2244-53. DOI:10.1161/CIRCULATIONAHA.110.990317 · 14.95 Impact Factor
  • Urology 04/2011; 77(4):1011–1012. DOI:10.1016/j.urology.2011.01.013 · 2.13 Impact Factor
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    Huichao Chen, Amita K Manatunga
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    ABSTRACT: We consider repeated measures interval-observed data with informative dropouts. We model the repeated outcomes via an unobserved random intercept and it is assumed that the probability of dropout during the study period is linearly related to the random intercept in a complementary log-log scale. Assuming the random effect follows the power variance function (PVF) family suggested by Hougaard (2000), we derive the marginal likelihood in a closed form. We evaluate the performance of the maximum likelihood estimation via simulation studies and apply the proposed method to a real data set.
    Statistics [?] Probability Letters 02/2011; 81(2):292-297. DOI:10.1016/j.spl.2010.10.012 · 0.53 Impact Factor
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    ABSTRACT: To address the fact that a decrease in the relative renal uptake of 99mTc-mercaptoacetyltriglycine (MAG3) on serial MAG3 scans may indicate a loss of function and require a change in management by providing guidance as to what constitutes a meaningful change in serial relative function measurements as well determining the normal variation of other common MAG3 renogram parameters. A prospective study was conducted in 24 male urology patients with stable renal function. The mean age was 66.5 ± 7.9 (SD) years; the mean serum creatinine was 1.38 ± 0.57 (SD) mg/dL, and the MAG3 renal scans were performed a mean of 11 ± 8 days apart. Each MAG3 scan included a measurement of relative function as well as the time to maximum counts and 20 minutes to maximum count ratios for both cortical and whole kidney regions of interest. The Pearson and intraclass correlations for the baseline and repeat measurements of relative renal function were both 0.98. Bland-Altman plots showed no bias between the baseline and repeat relative uptake measurements. The mean difference between 2 repeated measurements of the relative MAG3 uptake was 0.04 ± 2.88% (SD) for the left kidney and 0.08 ± 3.07% (SD) for the right kidney. Comparable results were obtained for the other renogram parameters. Measurements of relative renal uptake of MAG3 and common renogram parameters are highly reproducible; a decrease in relative uptake ≥7% (ie, 50%-43%) implies a loss in renal function.
    Urology 12/2010; 76(6):1512-6. DOI:10.1016/j.urology.2010.03.066 · 2.13 Impact Factor
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    Reneé H Moore, Robert H Lyles, Amita K Manatunga
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    ABSTRACT: When the prediction of subject-specific random effects is of interest, constrained Bayes predictors (CB) have been shown to reduce the shrinkage of the widely accepted Bayes predictor while still maintaining desirable properties, such as optimizing mean-square error subsequent to matching the first two moments of the random effects of interest. However, occupational exposure and other epidemiologic (e.g. HIV) studies often present a further challenge because data may fall below the measuring instrument's limit of detection. Although methodology exists in the literature to compute Bayes estimates in the presence of non-detects (Bayes(ND)), CB methodology has not been proposed in this setting. By combining methodologies for computing CBs and Bayes(ND), we introduce two novel CBs that accommodate an arbitrary number of observable and non-detectable measurements per subject. Based on application to real data sets (e.g. occupational exposure, HIV RNA) and simulation studies, these CB predictors are markedly superior to the Bayes predictor and to alternative predictors computed using ad hoc methods in terms of meeting the goal of matching the first two moments of the true random effects distribution.
    Statistics in Medicine 11/2010; 29(25):2656-68. DOI:10.1002/sim.4043 · 2.04 Impact Factor
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    ABSTRACT: The Michigan Female Health Study (MFHS) conducted research focusing on reproductive health outcomes among women exposed to polybrominated biphenyls (PBBs). In the work presented here, the available longitudinal serum PBB exposure measurements are used to obtain predictions of PBB exposure for specific time points of interest via random effects models. In a two-stage approach, a prediction of the PBB exposure is obtained and then used in a second-stage health outcome model. This paper illustrates how a unified approach, which links the exposure and outcome in a joint model, provides an efficient adjustment for covariate measurement error. We compare the use of empirical Bayes predictions in the two-stage approach with results from a joint modeling approach, with and without an adjustment for left- and interval-censored data. The unified approach with the adjustment for left- and interval-censored data resulted in little bias and near-nominal confidence interval coverage in both the logistic and linear model setting.
    Statistics in Medicine 07/2010; 29(16):1661-72. DOI:10.1002/sim.3905 · 2.04 Impact Factor

Publication Stats

3k Citations
426.74 Total Impact Points

Institutions

  • 1999–2015
    • Emory University
      • • Division of Cardiology
      • • Department of Biostatistics and Bioinformatics
      • • Department of Psychiatry and Behavioral Sciences
      • • Department of Radiology and Imaging Sciences
      Atlanta, Georgia, United States
  • 2007
    • University of Alabama at Birmingham
      Birmingham, Alabama, United States
  • 1992–1996
    • Indiana University-Purdue University Indianapolis
      • Department of Medicine
      Indianapolis, IN, United States
    • Indiana University-Purdue University School of Medicine
      • Department of Medicine
      Indianapolis, Indiana, United States
    • University of Indianapolis
      Indianapolis, Indiana, United States