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Deletion diagnostics for alternating logistic regressions

John S. Preisser, Kunthel By, Jamie Perin, Bahjat F. Qaqish
2012 Biometrical Journal  
Extensions of earlier work on GEE diagnostics follow directly, including computational formulae for one-step deletion diagnostics that measure the influence of a cluster of observations on the estimated  ...  Deletion diagnostics are introduced for the regression analysis of clustered binary outcomes estimated with alternating logistic regressions, an implementation of generalized estimating equations (GEE)  ...  Besides cluster-deletion diagnostics, we have developed and implemented in SAS/IML software observation-deletion diagnostics for ALR that approximate the change in regression coefficients when a single  ... 
doi:10.1002/bimj.201200002 pmid:22777960 pmcid:PMC3624608 fatcat:osdwiiijonco3apcc2k6kkepui

HLMdiag: A Suite of Diagnostics for Hierarchical Linear Models inR

Adam Loy, Heike Hofmann
2014 Journal of Statistical Software  
Over the last twenty years there have been numerous developments in diagnostic procedures for hierarchical linear models; however, these procedures are not widely implemented in statistical software packages  ...  The lack of availability of diagnostic procedures for hierarchical linear models has limited their adoption in statistical practice.  ...  to general statistical software packages.  ... 
doi:10.18637/jss.v056.i05 fatcat:fu4gsinpkralpayuv3qk5oapya

Influence diagnostics and outlier tests for semiparametric mixed models

Wing-Kam Fung, Zhong-Yi Zhu, Bo-Cheng Wei, Xuming He
2002 Journal of The Royal Statistical Society Series B-statistical Methodology  
We focus on influence measures for the fixed effects and provide formulae that are analogous to those for simpler models and readily computable with the MPLE algorithm.  ...  This paper considers the role of influence diagnostics in the MPLE by extending the case deletion and subject deletion analysis of linear models to accommodate the inclusion of a nonparametric component  ...  The authors thank Dr Daowen Zhang for sending them the data set and an SAS macro and two referees and an Associate Editor for constructive comments and helpful suggestions.  ... 
doi:10.1111/1467-9868.00351 fatcat:d3j766pqafdojmz5a3duaibqim

Model Diagnostics for Proportional and Partial Proportional Odds Models

Ann A. O'Connell, Xing Liu
2011 Journal of Modern Applied Statistical Methods  
Although widely used to assist in evaluating the prediction quality of linear and logistic regression models, residual diagnostic techniques are not well developed for regression analyses where the outcome  ...  The purpose of this article is to review methods of model diagnosis that may be useful in investigating model assumptions and in identifying unusual cases for PO and PPO models, and provide a corresponding  ...  Table 5 : 5 Residual Diagnostics of Logistic Regression in SPSS, SAS and Stata Types Of Residuals Mathematical Formula SPSS SAS Stata Pearson Residuals Table 6a : 6a Casewise Diagnostics for  ... 
doi:10.22237/jmasm/1304223240 fatcat:b55pywjew5dfvdg3ytxr5fefia

Case-Deletion Diagnostics for Quantile Regression Using the Asymmetric Laplace Distribution [article]

Luis E. Benites, Víctor H. Lachos, Filidor E. Vilca
2015 arXiv   pre-print
We develop a case-deletion diagnostic analysis for QR models based on the conditional expectation of the complete-data log-likelihood function related to the EM algorithm.  ...  To make inferences about the shape of a population distribution, the widely popular mean regression model, for example, is inadequate if the distribution is not approximately Gaussian (or symmetric).  ...  In order to identify influential observations at different quantiles when some observation is eliminated, we can generate graphs of the generalized Cook distance GD l i , as explained in Section 3.  ... 
arXiv:1509.05099v1 fatcat:6qwmwklhpneoboktglmoyqezfa

Statistical Software and Regression Diagnostic Reporting with Fuzzy-AHP Intelligent Zax (FAIZ)

Shahid Anjum
2014 Lecture Notes on Software Engineering  
In this study Fuzzy AHP Intelligent Zax (FAIZ) has been proposed which can be incorporated in statistical software as a scoring technique for ranking the simple linear regressions (SLR) based on fuzzy  ...  Analytical Hierarchy Process (AHP) logic to push 'Further Evolution' in Software Engineering Evolution process for Statistical Software.  ...  Finally compute the "average RO" (ARO) of MM-α-RO and MM-β-RO for each alternative regression. Robustness score for simulated data (RSSD) replaces validation data with simulated data.  ... 
doi:10.7763/lnse.2014.v2.92 fatcat:zlwy7nt4kndmblh2b3crg5xcaa

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

Filidor V. Labra, Aldo M. Garay, Victor H. Lachos, Edwin M.M. Ortega
2012 Journal of Statistical Planning and Inference  
We derive a simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters and the observed information matrix is derived analytically.  ...  This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2009 ) since the random terms distributions cover both symmetric  ...  are available in softwares as SAS, R, Ox and Matlab.  ... 
doi:10.1016/j.jspi.2012.02.018 fatcat:hkzc6yvesrcalhuivnqpj656qq

Sample Size Requirements for Applying Diagnostic Classification Models

Sedat Sen, Allan S. Cohen
2021 Frontiers in Psychology  
Item parameter and classification accuracy were higher for DINA and DINO models.  ...  Effects were evaluated using bias and RMSE computed between true (i.e., generating) parameters and estimated parameters.  ...  General DCMs include the log-linear cognitive diagnostic model (LCDM; Henson et al., 2009) , the general diagnostic model (GDM; von Davier, 2005) , and the generalized DINA (G-DINA; de la Torre, 2011  ... 
doi:10.3389/fpsyg.2020.621251 pmid:33569029 pmcid:PMC7868330 fatcat:v47dv2e5nzbwhkfo3xsykaqt54

Diagnostic with incomplete nominal/discrete data

Herbert F. Jelinek, Andrew Yatsko, Andrew Stranieri, Sitalakshmi Venkatraman, Adil Bagirov
2015 Artificial intelligence research  
Missing values may be present in data without undermining its use for diagnostic / classification purposes but compromise application of readily available software.  ...  Discretization of continuous attributes renders all data nominal and is helpful in dealing with missing values; particularly, no special handling is required for different attribute types.  ...  [1] Many statistical software packages implement EM and MI: SPSS, SAS, to name a few.  ... 
doi:10.5430/air.v4n1p22 fatcat:uj7sdkoisngujhcnhvjxzgaaje

COMPARISONS BETWEEN ROBUST REGRESSION APPROACHES IN THE PRESENCE OF OUTLIERS AND HIGH LEVERAGE POINTS

Anwar Fitrianto, Sim Hui Xin
2022 BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN  
The study aimed to compare a few robust approaches in linear regression in the presence of outlier and high leverage points.  ...  However, some fundamental assumptions must be fulfilled to provide good parameter estimates for the OLS estimation.  ...  The regression model for the Milk Production data is CURRENT= 0  + 1  PREVIOUS+ 3  DAYS+  . The Statistical Analysis Software (SAS) is used to assist in the computation.  ... 
doi:10.30598/barekengvol16iss1pp241-250 fatcat:vrjbqy52izat5dxyvdw6jrxrva

A distribution-free smoothed combination method of biomarkers to improve diagnostic accuracy in multi-category classification [article]

Raju Maiti, Jialiang Li, Priyam Das, Lei Feng, Derek Hausenloy, Bibhas Chakraborty
2019 arXiv   pre-print
With the above smooth approximations, efficient gradient-based algorithms can be employed to obtain better solution with less computing time.  ...  In this article, we develop a linear combination method that maximizes a smooth approximation of the empirical Hypervolume Under Manifolds (HUM) for multi-category outcome.  ...  Acknowledgements We thank Jon Wellner, Palash Ghosh and Heerajnarain Bulluck for helpful discussions.  ... 
arXiv:1904.10046v1 fatcat:glkbngcq2jgbzefaix372a363m

Toward a diagnostic toolkit for linear models with Gaussian-process distributed random effects [article]

Maitreyee Bose, James S. Hodges, Sudipto Banerjee
2018 arXiv   pre-print
Second, to examine the data's support for a covariate and to understand how adding that covariate moves variation in the outcome y out of the GP and error parts of the fit, we apply a linear-model diagnostic  ...  likelihood for a gamma-errors GLM with identity link.  ...  In this regard we note that all diagnostics for non-normal generalized linear models and for Cox regression are based on approximations.  ... 
arXiv:1805.01010v1 fatcat:75og37e2yfdddgafh4hqxdwwp4

Partial least squares regression in the social sciences

Megan L. Sawatsky, Matthew Clyde, Fiona Meek
2015 The Quantitative Methods for Psychology  
linear regression, principal component regression); and apply the technique to a hypothetical dataset using JMP statistical software (with references to SAS software).  ...  Here, we provide a brief introduction to PLSR, directed towards a novice audience with limited exposure to the technique; demonstrate its utility as an alternative to more classic approaches (multiple  ...  In this example, figures and outputs are generated using JMP version 10 software; references to SAS version 9.3 are made throughout.  ... 
doi:10.20982/tqmp.11.2.p052 fatcat:oije6mdfkbcxzmq7bsy6domlfu

Accounting for Complex Sampling in Survey Estimation: A Review of Current Software Tools

Brady T. West, Joseph W. Sakshaug, Guy Alain S. Aurelien
2018 Journal of Official Statistics  
We conclude with a summary of directions for future software development in this area.  ...  We present brief overviews of the similarities and differences between these alternative approaches, and then focus on software tools that are presently available for implementing each approach.  ...  Software packages and specific procedures capable of implementing these "hybrid" approaches for both linear and generalized linear regression models include Stata (Version 15.1þ ), SAS (PROC GLIMMIX, SAS  ... 
doi:10.2478/jos-2018-0034 fatcat:uvenufveczcmtb4vjehsygra5u

15th International Nutrition and Diagnostics Conference INDC 2015

2016 Integrative Food Nutrition and Metabolism  
Polynominal regression model with linear and quadratic terms was used for the statistic analysis of the experimental data.  ...  Relationship between sleep duration and obesity-related variables or dietary macronutrients intake was examined using multiple variable logistic regression models and general linear models after adjustment  ...  Sorghum is a gluten-free cereal that is a safe alternative for people with celiac disease and gluten intolerance. It also presents a variety of other health benefits.  ... 
doi:10.15761/ifnm.1000159 fatcat:4klmvcr7endlloi6fmuwn333ri
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