[PDF] Top 20 Instrumental variable estimation in binary measurement error models
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Instrumental variable estimation in binary measurement error models
... linear measurement error model instrumental variable estimator is presented and used to motivate the generalization to binary regression models.. Results of a simulation study are discus[r] ... See full document
21
Orthogonal Series Estimation of Nonparametric Regression Measurement Error Models with Validation Data
... regression measurement error model with the availability of a validation data ...the models considered by the above referenced authors are some parametric or semiparametric models, and the ... See full document
12
Estimation and Inference of Threshold Regression Models with Measurement Errors
... Measurement error is a common problem in economic ...to measurement errors because of data aggregation or for other ...of measurement errors results in inconsistent estimation of ... See full document
27
Estimation of Nonparametric Multiple Regression Measurement Error Models with Validation Data
... the instrumental variable method (see, ...function estimation with surrogate data and validation ...surrogate variable are ...explanatory variable vectors can consist of va- riables ... See full document
12
Mathematical reflection approach to instrumental variable estimation method for simple regression model
... the measurement error problem since 1920 is the instrumental variables approach (see Goldberger (1972) for a historical ...variables estimation methods and their applications in finance ... See full document
21
Estimation of Nonparametric Regression Models with Measurement Error Using Validation Data
... The relationship between the true variable and the surrogate variable can be rather complicated. Misspecification of this relationship may lead to a serious misinterpretation of the data. Common solution is ... See full document
10
Instrumental variable estimation in generalized linear measurement error models
... The problem of finding efficient, consistent estimators of parameters for a general regression function in the presence of covariate measurement error has not been solved. The problem wi[r] ... See full document
115
Robust Estimation via Measurement Error Modeling
... statistical models that are not easily robustified using standard approaches, such as time series ...hard-to-robustify models that piqued our interest in the error modeling approach, and this is ... See full document
102
Instrumental Variable Estimation of Dynamic Linear Panel Data Models with Defactored Regressors under Cross sectional Dependence
... consistent estimation methods and making asymptotically valid inferences, has proven both popular and ...spatial models based on the method of maximum likelihood ...factor error structure may be ... See full document
28
Unbiased estimation of a nonlinear function of a normal mena with application to measurement-error models
... Key Words and Phrases: errors-in-variables; functional models; generalized linear model; H-estimation; measurement error; structural IIIOdels; unbiased estimation... ABSTRACT.[r] ... See full document
26
Control Function Instrumental Variable Estimation of Nonlinear Causal Effect Models
... Our simulation study compares the usual two stage least squares (2SLS) estimator, the control function (CF) estimator and the pretest estimator. We will consider several differ- ent model settings where the assumptions ... See full document
35
Instrumental variable estimation in semi parametric additive hazards models
... Instrumental variable methods allow unbiased estimation in the presence of unmeasured con- founders when an appropriate instrumental variable is ...hazard models for censored ... See full document
17
Measurement error in assessment
... response and should be flagged if the item is answered correctly. The 3PL IRT model incorporates a pseudo chance parameter which is often interpreted as indicative of guessing. Whether CTT, Rasch or IRT is used, MCQs are ... See full document
5
Sequential regression measurement error models with application
... logistic measurement error regression’ (Model 3) with ‘na¨ive sequential logistic regression’ (Model 1) and ‘sequential logistic regression’ (Model 2) and (b) briefly describe some tactical implications for ... See full document
24
Consistent estimation in an implicit quadratic measurement error model
... Using the noise model assumptions, we apply an adjustment procedure, see Naidu (1990), that takes into account the quadratic structure of the model and cor- rects the OLS estimate appropriately. The resulting estimator, ... See full document
25
Instrumental Variable Estimates of the Effect of Management Practices on Firm Performance in Korean Firms
... of instrumental variables given the null hypothesis of equality of the distributions of management practice scores in Figure ...of instrumental variables is statistically and significantly associated with ... See full document
19
Instrumental Variable and Propensity Score Methods for Bias Adjustment in Non-Linear Models
... However, the consistency of the two stage IV estimators in the context of nonlinear models remains unclear. Terza, Basu, and Rathouz, 2008 constructed a two stage nonlinear modeling framework to account for ... See full document
117
Asymptotic Performance of the Location and Logistic Classification Rules for Multivariate Binary Variables
... computed error rate was used to calculate the relative error of the ...relative error of the rule became three times more important from homoscedastic to ... See full document
7
Testing for unit roots in autoregressive moving average models: An instrumental variable approach
... In this paper we have proposed a test for a unit root in autoregressive moving average time series models based on an instrumental variable estimator. The main advantage of the instrumen[r] ... See full document
27
Latent variable models for binary response data
... An interesting set of results was given by the two-parameter and the three-parameter model with c-0 (guessing parameter). Even though the numerical values of the difficulty and the discrimination parameters would be the ... See full document
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