Covariates that may be used
Propensity score analysis with partially observed covariates: How should multiple imputation be used?
... the covariates (equation ...balance covariates between groups. MIps and MIpar create a single overall PS used to estimate the treatment ...the covariates in the original incomplete ...PS ...
43
Propensity score analysis with partially observed covariates: How should multiple imputation be used?
... widely used in marginal structural models (MSMs) to handle time-dependent ...issues may arise with IPTW when some estimated weights are too extreme; PS matching can be a better solution in this context ...
43
High-Dimensional Covariates
... The function PGEE returns an object class of PGEE. Applying the functions print and summary to an object returned by function PGEE provides detailed information related to the model fitting and summarizes the results as ...
10
Regression discontinuity design with covariates
... The regression discontinuity design is a method frequently used in treatment evaluation, when certain e.g. bureaucratic rules imply a threshold at which many subjects change their treatment status. Consider a law ...
27
Accommodating Covariates in ROC Analysis
... The final step is to plot and compare the ROC curves for the linear predictions from the two models. This can be accomplished using the programs roccurve and comproc. This procedure is simplistic in at least two ...
25
Regression discontinuity design with covariates
... The regression discontinuity design is a method frequently used in treatment evaluation, when certain e.g. bureaucratic rules imply a threshold at which many subjects change their treatment status. Consider a law ...
24
Semiparametric Estimation with Generated Covariates
... Generated Covariates in Semiparametric Models We consider a general class of semiparametric optimization estimators where the criterion function depends on two types of infinite dimensional nuisance parameters: a ...
44
Estimating occupational mobility with covariates
... is used on an intergenerational transition matrix constructed from the Norwegian censuses of 1960 and ...those used by Long & Ferrie (2013); see Modalsli (2015) for further ...
14
Bayesian Imputation of Missing Covariates
... commonly used (base) R ...incomplete covariates, analysis and imputation can be performed simultaneously while assuring compatibility between all sub- models (Erler, Rizopoulos, Rosmalen, et ...incomplete ...
265
A sparse ising model with covariates
... The first two columns of each covariate-related columns are the node names and the third column records the selection frequency. There are 348 inter-chromosome interactions (between cy- tobands from different chromosomes) ...
11
Nonparametric Regression with Nonparametrically Generated Covariates
... Our main result can e.g. directly be used to establish asymptotic normality or uniform rates of consistency of the estimate of m 0 . Furthermore, we can derive a formula for the asymptotic variance that accounts ...
48
Qml inference for volatility models with covariates
... tests used to identify the order p and q are also non standard (see ...the covariates can be for instance lagged values of other squares returns, or realized volatilities, or positive and negative parts of ...
40
Statistical Methods for Networks with Node Covariates
... We used all the data except for period 6 as it contains much fewer nodes comparing to previous ...The covariates we used include gender, age, marital status, attending university or not, brigade ...
127
Missing ordinal covariates with informative selection
... Column 4 of Table 8 reports results from the missing covariate model and the extra controls specification. This specification exploits linkage of three datasets, NPD, LSYPE, and 2001 UK Census. As we discussed earlier, ...
47
Semiparametric Regression Models for Interacting Covariates.
... we used parametric guides to enhance the performance of nonparametric estima- tors of the parameter functions in varying coefficient ...was used, and lower bias and variance when the optimal bandwidth was ...
84
A review on ROC curves in the presence of covariates
... the covariates and using a classifica- tion rule that relies on a common threshold value, will result in the test having a discriminatory capacity that is biased compared to its ‘true potential’ discrimina- tory ...
21
Beyond Traditional Covariates in Medical Informatics
... patient’s covariates (including his or her DBCs) are used to query a predictive model to help the physician choose the potentially most efficient ...patients, covariates, and ...rate may ...
12
Survival models with gene groups as covariates
... Clinical covariates like age, gender, blood pressure, tumor size and grade, as well as smoking and drinking history have been extensively used and shown to have satisfactory predictive ...traditionally ...
81
Matched Bipartite Block Model with Covariates
... We have applied the algorithm to two wikipedia page–user networks, which we will call TopAr- ticles and Cities . Each is a bipartite network between a collection of Wikipedia pages and the users who edited them: An edge ...
44
Mixtures of factor analyzers: an extension with covariates
... algorithm used for the maximum likelihood estimation of parameters and the estimation of both ex- pected factor scores and posterior class membership for artificial and real ...
15