Sampling, WLS, and Mixed Models

Mixed models may be defined with or without reference to sampling, and can be used to predict realized random effects, as when estimating the latent values of study subjects measured with response error. When the model is specified without reference to sampling, a simple mixed model includes two random variables, one stemming from an exchangeable distribution of latent values of study subjects and the other, from the study subjects` response error distributions. Positive probabilities are assigned to both potentially realizable responses and artificial responses that are not potentially realizable, resulting in artificial latent values. In contrast, finite population mixed models represent the two-stage process of sampling subjects and measuring their responses, where positive probabilities are only assigned to potentially realizable responses. A comparison of the estimators over the same potentially realizable responses indicates that the optimal linear mixed model estimator (the usual best linear unbiased predictor, BLUP) is often (but not always) more accurate than the comparable finite population mixed model estimator (the FPMM BLUP). We examine a simple example and provide the basis for a broader discussion of the role of conditioning, sampling, and model assumptions in developing inference.

Leverage analysis for linear mixed models

We consider a generalized leverage matrix useful for the identification of influential units and observations in linear mixed models and show how a decomposition of this matrix may be employed to identify high leverage points for both the marginal fitted values and the random effect component of the conditional fitted values. We illustrate the different uses of the two components of the decomposition with a simulated example as well as with a real data set.

Improved testing inference in mixed linear models

Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit. Often, the number of observations is small, and it is thus important to use inference strategies that incorporate small sample corrections. In this paper, we develop modified versions of the likelihood ratio test for fixed effects inference in mixed linear models. In particular, we derive a Bartlett correction to such a test, and also to a test obtained from a modified profile likelihood function. Our results generalize those in [Zucker, D.M., Lieberman, O., Manor, O., 2000. Improved small sample inference in the mixed linear model: Bartlett correction and adjusted likelihood. Journal of the Royal Statistical Society B, 62,827-838] by allowing the parameter of interest to be vector-valued. Additionally, our Bartlett corrections allow for random effects nonlinear covariance matrix structure. We report simulation results which show that the proposed tests display superior finite sample behavior relative to the standard likelihood ratio test. An application is also presented and discussed. (C) 2008 Elsevier B.V. All rights reserved.

Likelihood ratio tests for variance components in linear mixed models

Although the asymptotic distributions of the likelihood ratio for testing hypotheses of null variance components in linear mixed models derived by Stram and Lee [1994. Variance components testing in longitudinal mixed effects model. Biometrics 50, 1171-1177] are valid, their proof is based on the work of Self and Liang [1987. Asymptotic properties of maximum likelihood estimators and likelihood tests under nonstandard conditions. J. Amer. Statist. Assoc. 82, 605-610] which requires identically distributed random variables, an assumption not always valid in longitudinal data problems. We use the less restrictive results of Vu and Zhou [1997. Generalization of likelihood ratio tests under nonstandard conditions. Ann. Statist. 25, 897-916] to prove that the proposed mixture of chi-squared distributions is the actual asymptotic distribution of such likelihood ratios used as test statistics for null variance components in models with one or two random effects. We also consider a limited simulation study to evaluate the appropriateness of the asymptotic distribution of such likelihood ratios in moderately sized samples. (C) 2008 Elsevier B.V. All rights reserved.

Local Influence Analysis for Skew-Normal Linear Mixed Models

In this article, we consider local influence analysis for the skew-normal linear mixed model (SN-LMM). As the observed data log-likelihood associated with the SN-LMM is intractable, Cook`s well-known approach cannot be applied to obtain measures of local influence. Instead, we develop local influence measures following the approach of Zhu and Lee (2001). This approach is based on the use of an EM-type algorithm and is measurement invariant under reparametrizations. Four specific perturbation schemes are discussed. Results obtained for a simulated data set and a real data set are reported, illustrating the usefulness of the proposed methodology.

Predicting random effects with an expanded finite population mixed model

Prediction of random effects is an important problem with expanding applications. In the simplest context, the problem corresponds to prediction of the latent value (the mean) of a realized cluster selected via two-stage sampling. Recently, Stanek and Singer [Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 119-130] developed best linear unbiased predictors (BLUP) under a finite population mixed model that outperform BLUPs from mixed models and superpopulation models. Their setup, however, does not allow for unequally sized clusters. To overcome this drawback, we consider an expanded finite population mixed model based on a larger set of random variables that span a higher dimensional space than those typically applied to such problems. We show that BLUPs for linear combinations of the realized cluster means derived under such a model have considerably smaller mean squared error (MSE) than those obtained from mixed models, superpopulation models, and finite population mixed models. We motivate our general approach by an example developed for two-stage cluster sampling and show that it faithfully captures the stochastic aspects of sampling in the problem. We also consider simulation studies to illustrate the increased accuracy of the BLUP obtained under the expanded finite population mixed model. (C) 2007 Elsevier B.V. All rights reserved.

A note on influence diagnostics in nonlinear mixed-effects elliptical models

This paper provides general matrix formulas for computing the score function, the (expected and observed) Fisher information and the A matrices (required for the assessment of local influence) for a quite general model which includes the one proposed by Russo et al. (2009). Additionally, we also present an expression for the generalized leverage on fixed and random effects. The matrix formulation has notational advantages, since despite the complexity of the postulated model, all general formulas are compact, clear and have nice forms. (C) 2010 Elsevier B.V. All rights reserved.

Saliva flow rate, buffer capacity, and pH of autistic individuals

The objective of the study was to evaluate saliva flow rate, buffer capacity, pH levels, and dental caries experience (DCE) in autistic individuals, comparing the results with a control group (CG). The study was performed on 25 noninstitutionalized autistic boys, divided in two groups. G1 composed of ten children, ages 3-8. G2 composed of 15 adolescents ages 9-13. The CG was composed of 25 healthy boys, randomly selected and also divided in two groups: CG3 composed of 14 children ages 4-8, and CG4 composed of 11 adolescents ages 9-14. Whole saliva was collected under slight suction, and pH and buffer capacity were determined using a digital pHmeter. Buffer capacity was measured by titration using 0.01 N HCl, and the flow rate expressed in ml/min, and the DCE was expressed by decayed, missing, and filled teeth (permanent dentition [DMFT] and primary dentition [dmft]). Data were plotted and submitted to nonparametric (Kruskal-Wallis) and parametric (Student`s t test) statistical tests with a significance level less than 0.05. When comparing G1 and CG3, groups did not differ in flow rate, pH levels, buffer capacity, or DMFT. Groups G2 and CG4 differ significantly in pH (p = 0.007) and pHi = 7.0 (p = 0.001), with lower scores for G2. In autistic individuals aged 3-8 and 9-13, medicated or not, there was no significant statistical difference in flow rate, pH, and buffer capacity. The comparison of DCE among autistic children and CG children with deciduous (dmft) and mixed/permanent decayed, missing, and filled teeth (DMFT) did not show statistical difference (p = 0.743). Data suggest that autistic individuals have neither a higher flow rate nor a better buffer capacity. Similar DCE was observed in both groups studied.

Perspectives for Novel Mixed Diruthenium-Organic Drugs as Metallopharmaceuticals in Cancer Therapy

Ruthenium compounds have been actively studied as metallodrugs for cancer therapy. Representatives of ruthenium-based antitumor drugs are the classes of ruthenium(III)-chlorido-(N-ligand)complexes, including the drugs namely NAMI-A and KP1019 in clinical trials, and ruthenium(II)-arene organometallics, with some compounds currently undergoing advanced preclinical testing. An alternative approach for tumor-inhibiting metallodrugs is the coordination of metal ions to organic pharmaceuticals. The combination of antitumor-active ruthenium ion with biologically-active pro-ligands in single compounds can result in the enhancement of activity, for example through synergistic effects. In the present article, some developments in the ruthenium-based antitumor drugs field are briefly highlighted and recent studies on mixed diruthenium-organic drugs as metallopharmaceuticals in cancer therapy are described. Novel organic pharmaceuticals-containing diruthenium(II, III)complexes have shown promising antitumor activity for C6 rat glioma - a model for glioblastoma multiforme (GBA).

Designing Novel Antitrypanosomal Agents from a Mixed Graph-Theoretical Substructural Approach

Chagas disease is nowadays the most serious parasitic health problem. This disease is caused by Trypanosoma cruzi. The great number of deaths and the insufficient effectiveness of drugs against this parasite have alarmed the scientific community worldwide. In an attempt to overcome this problem, a model for the design and prediction of new antitrypanosomal agents was obtained. This used a mixed approach, containing simple descriptors based on fragments and topological substructural molecular design descriptors. A data set was made up of 188 compounds, 99 of them characterized an antitrypanosomal activity and 88 compounds that belong to other pharmaceutical categories. The model showed sensitivity, specificity and accuracy values above 85%. Quantitative fragmental contributions were also calculated. Then, and to confirm the quality of the model, 15 structures of molecules tested as antitrypanosomal compounds (that we did not include in this study) were predicted, taking into account the information on the abovementioned calculated fragmental contributions. The model showed an accuracy of 100% which means that the ""in silico"" methodology developed by our team is promising for the rational design of new antitrypanosomal drugs. (C) 2009 Wiley Periodicals, Inc. J Comput Chem 31: 882-894. 2010

Synthesis, characterization and adsorption properties of porous mixed valent diruthenium(II,III)-terephthalate and diruthenium(II,III)-adipate polymers

Two porous mixed valent diruthenium(II,III)-dicarboxylate compounds have been prepared and characterized by spectroscopic methods, X-ray diffraction and thermogravimetry. Crystalline solids of [Ru(2)(tere)(2)Cl] center dot 3.5H(2)O (tere=terephthalate) and [Ru(2)(adip)(2)Cl] center dot 1.5H(2)O (adip=adipate) consist of extended chains in which polymeric layers of multiply metal-metal bonded [Ru(2)](5+) cores are bridged by dicarboxylate ligands in paddlewheel type geometries. Units of [Ru(2)(dicarboxylate)(2)](n)(+) are linked by axial bridging chloride ions generating three-dimensional networks. The polymers loose non-bonded water molecules at low temperatures but do not undergo thermal decomposition below 280-300 degrees C. Both of compounds exhibit high BET surface areas, [Ru(2)(tere)(2)Cl]: 235 m(2) g(-1) and [Ru(2)(adip)(2)Cl]: 281 m(2) g(-1), and occlude similar numbers of mol of N(2) per mol of metal. The terephthalate ligand generated an organized structure with supermicropores (total pore size of 0.24 cm(3) g(-1)) while the adipate ligand led to a mesoporous structure (total pore sizes of 0.47 cm(3) g(-1)) for the corresponding diruthenium(II,III)-dicarboxylate polymers. (c) 2008 Elsevier B.V. All rights reserved.

Microwave-Assisted Derivatization of Cellulose in an Ionic Liquid: An Efficient, Expedient Synthesis of Simple and Mixed Carboxylic Esters

Microwave (MW)-assisted cellulose dissolution in ionic liquids (ILs) has routinely led either to incomplete biopolymer solubilization, or its degradation. We show that these problems can be avoided by use of low-energy MW heating, coupled with efficient stirring. Dissolution of microcrystalline cellulose in the IL 1-allyl-3-methylimidazolium chloride has been achieved without changing its degree of polymerization; regenerated cellulose showed pronounced changes in its index of crystallinity, surface area, and morphology. MW-assisted functionalization of MCC by ethanoic, propanoic, butanoic, pentanoic, and hexanoic anhydrides has been studied. Compared with conventional heating, MW irradiation has resulted in considerable decrease in dissolution and reaction times. The value of the degree of substitution (DS) was found to be DS(ethanoate) > DS(propanoate) > DS(butanoate). The values of DS(pentanoate) and DS(hexanoate) were found to be slightly higher than DS(ethanoate). This surprising dependence on the chain length of the acylating agent has been reported before, but not rationalized. On the basis of the rate constants and activation parameters of the hydrolysis of ethanoic, butanoic, and hexanoic anhydrides in aqueous acetonitrile (a model acyl transfer reaction), we suggest that this result may be attributed to the balance between two opposing effects, namely, steric crowding and (cooperative) hydrophobic interactions between the anhydride and the cellulosic surface, whose lipophilicity has increased, due to its partial acylation. Four ethanoate-based mixed esters were synthesized by the reaction with a mixture of the two anhydrides; the ethanoate moiety predominated in all products. The DS is reproducible and the IL is easily recycled. (C) 2009 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 48: 134-143, 2010

Mixed-Ligand Complexes of Technetium and Rhenium with Tridentate Benzamidines and Bidentate Benzoylthioureas

Mixed-ligand complexes of technetium(V) or rhenium(V) containing tridentate N-[(dialkylamino)(thiocarbonyl)]benzamidine (H(2)L(1)) and bidentate N,N-dialkyl-N`-benzoylthiourea (HL(2)) ligands were formed in high yields when (NBu(4))[MOCl(4)] (M = Tc or Re) or [ReOCl(3)(PPh(3))(2)] was treated with mixtures of the proligands. Other approaches for the synthesis of the products are reactions of [MOCl(L(1))] complexes with HL(2) or compounds of the-composition [ReOCl(2)(PPh(3))(L(2))] with H(2)L(1). The resulting air-stable [MO(L(1))(L(2))] complexes possess potential for the development of metal-based radiopharmaceuticals. [TcO(L(1))(L(2))] complexes are readily reduced by PPh3 with formation of [Tc(L(1))(L(2))(PPh(3))]. The resulting Tc(III) complexes undergo two almost-reversible oxidation steps corresponding to one-electron transfer processes. ((C) Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2009)

The Mixed-Method Library: Qualitative Research and the Future of Assessment in Higher Education

This presentation was offered as part of the CUNY Library Assessment Conference, Reinventing Libraries: Reinventing Assessment, held at the City University of New York in June 2014.

Feasible estimation of generalized linear mixed models (GLMM) with weak dependency between groups

This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with the random effects being correlated between groups. The core idea is to deal with the intractable integrals in the likelihood function by multivariate Taylor's approximation. The accuracy of the estimation technique is assessed in a Monte-Carlo study. An application of it with a binary response variable is presented using a real data set on credit defaults from two Swedish banks. Thanks to the use of two-step estimation technique, the proposed algorithm outperforms conventional pseudo likelihood algorithms in terms of computational time.