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Showing 1 to 20 of 876 for “"covariates"”.
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Recurrent Event Data Analysis with Mismeasured Covariates
… event time regression models accounting for the covariates. To circumvent the problem of bias and consistency associated with model's parameter estimation in the presence of measurement errors, we propose inference for corrected estimating functions with well-behaved roots under additive …
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Generalized Linear Models with Nonignorable Missing Covariates
… (GLMs) for binary and count data with missing covariates when the missing data mechanism is nonignorable. We use the maximum likelihood method to estimate the parameters in GLMs. We study a set of ML estimating equations for fitting regression models to binary and Poisson data with missing …
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Data-driven dynamic optimization with auxiliary covariates
Optimization under uncertainty forms the foundation for many of the fundamental problems the operations research community seeks to solve. In this thesis, we develop and analyze algorithms that incorporate ideas from machine learning to optimize uncertain objectives directly from data. In the first …
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Covariates of Return of Spontaneous Circulation (ROSC) in Adults
<p><strong>Background: </strong>Despite advancements in resuscitation efforts, sudden cardiac arrest remains the third leading cause of death in the United States, with approximately 200,000 adult cardiac arrests occurring in the hospital setting. Nearly 50% of the patients who experience an …
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Knowledge Discovery from Complex Event Time Data with Covariates
… novel methods of statistical analysis. Handling covariates properly while managing the missing values is a challenging task. These type of issues happen frequently in reliability data analysis. Specifically, accelerated life testing (ALT) data are usually conducted by exposing test units of a …
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Modelling covariates of infant and child mortality in Malawi
… 2011). Studies have been conducted to identify covariates of infant and child mortality in Malawi but none of these used recent data and none has included HIV/AIDS as a risk factor (Baker 1999; Bolstad and Manda 2001; Kalipeni 1992; Manda 1999). This study aims at examining bio-demographic, …
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Approaches for Handling Time-Varying Covariates in Survival Models
… a need to consider time-varying effects of the covariates. Several models have been developed that relax the proportionality assumption making it possible to analyse data with time-varying effects of both baseline and time-updated covariates. I present various approaches for handling …
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Estimation of Important Scenic Beauty Covariates from Remotely Sensed Data
The overall objective of this study was to determine if remotely sensed data could be used to model scenic beauty. Terrestrial digital images from within forest stands located in Prince Edward Gallion State Forest near Farmville, Virginia were rated for their scenic beauty by a group of students to …
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Aggressive antisocial behavior- clinical, cognitive, and behavioral covariates of its persistence
… The overall aim of the thesis was to establish covariates of persistent aggressive antisocial behavior in a population-based cohort and in clinically evaluated, prospectively followed, offender groups. Specific aims were: (1) to quantify the persistence of aggressive antisocial behavior, (2) to …
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Statistical Modeling and Predictions Based on Field Data and Dynamic Covariates
… general path model to incorporate dynamic covariates into degradation data analysis. Dynamic covariates include time-varying environmental variables and usage condition. The shapes of the effect functions of covariates may be constrained to be, for example, monotonically increasing (i.e., …
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Large-Sample Logistic Regression with Latent Covariates in a Bayesian Networking Context
… logistic regression when the most important covariates such as the college variables are latent, but the network structure is known. This network structure specifies the relationship between pre-college to college variables and then from college to student retention variables. Based on this …
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The Effects of Measurement Error on Analysis of Covariance With Multiple Covariates
Made available in DSpace on 2014-12-12T19:54:47Z (GMT). No. of bitstreams: 1 7714988.pdf: 5995058 bytes, checksum: 27f11cf6be4caf8daae09506c90a6d0d (MD5) Previous issue date: 1977
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The role of covariates on inferring the Q-matrix and learning trajectory
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2023-12-01
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Quantifying the Effects of Correlated Covariates on Variable Importance Estimates from Random Forests
Recent advances in computing technology have lead to the development of algorithmic modeling techniques. These methods can be used to analyze data which are difficult to analyze using traditional statistical models. This study examined the effectiveness of variable importance estimates from the …
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Unified Approach to Partially Linear Model and Cox Proportional Hazards Model with Missing Covariates
… hazards model (Cox, 1972) with missing covariates. The unified approach possesses some superior characteristics in dealing with regression models with missing data. First, the unified approach requires less extra assumptions to be applied than many other methods, which may need …
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Dealing with measurement error in covariates with special reference to logistic regression model: a flexible parametric approach
… between some explanatory variables or covariates and a response or outcome variable through a suitable regression model. The accuracy of such quantification depends on how precisely we measure the relevant covariates. In many instances, we can not measure some of the covariates …
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On the Use of Covariates in a Latent Class Signal Detection Model, with Applications to Constructed Response Scoring
… of the latent class SDT model to include covariates and examined the performance of the resulting model. Covariates can be incorporated into the latent class SDT model in three ways: 1) to affect latent class membership, 2) conditional response probabilities and 3) both latent class …
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Politics and pandemics: an investigation of the potential covariates in the relationship between conservative political ideology and reduced facemask wearing
… identity, mask wearing, and the hypothesized covariates. A simple regression model showed a significant negative relationship between conservative political identity and mask wearing. A multiple regression model including the hypothesized covariates showed that the inclusion of these variables …
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Comparison of the Item Response Theory with Covariates Model and Explanatory Cognitive Diagnostic Model for Detecting and Explaining Differential Item Functioning
… latent traits using relevant observed or latent covariates. If an item exhibits DIF which disadvantages a subgroup, covariates can be modeled to explain the DIF and indicate either true or spurious differences. If an item exhibited statistically significant DIF which became nonsignificant after …
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Relationships between binge eating, psychological and behavioral covariates, and health care utilization on college campuses: Results from a national sample of college students
<p>The purpose of this investigation was to examine the factors which moderate service utilization among college students, as well as risk factors for binge eating disorder (BED). Candidate moderators included binge eating, obesity, gender, ethnicity, psychological comorbidity, body image, and …
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