Does higher hospital cost imply higher quality of care?

This study investigates whether higher input use per stay in the hospital (treatment intensity) and longer length of stay improve outcomes of care. We allow for endogeneity of intensity and length of stay by estimating a quasi-maximum-likelihood discrete factor model, where the distribution of the unmeasured variable is modeled using a discrete distribution. Data on elderly persons come from several waves of the National Long-Term Care Survey merged with Medicare claims data for 1984-1995 and the National Death Index. We find that higher intensity improves patient survival and some dimensions of functional status among those who survive.

Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem

This paper studies the multiplicity-correction effect of standard Bayesian variable-selection priors in linear regression. Our first goal is to clarify when, and how, multiplicity correction happens automatically in Bayesian analysis, and to distinguish this correction from the Bayesian Ockham's-razor effect. Our second goal is to contrast empirical-Bayes and fully Bayesian approaches to variable selection through examples, theoretical results and simulations. Considerable differences between the two approaches are found. In particular, we prove a theorem that characterizes a surprising aymptotic discrepancy between fully Bayes and empirical Bayes. This discrepancy arises from a different source than the failure to account for hyperparameter uncertainty in the empirical-Bayes estimate. Indeed, even at the extreme, when the empirical-Bayes estimate converges asymptotically to the true variable-inclusion probability, the potential for a serious difference remains. © Institute of Mathematical Statistics, 2010.

Neuroimaging assessment of early and late neurobiological sequelae of traumatic brain injury: implications for CTE.

Traumatic brain injury (TBI) has been increasingly accepted as a major external risk factor for neurodegenerative morbidity and mortality. Recent evidence indicates that the resultant chronic neurobiological sequelae following head trauma may, at least in part, contribute to a pathologically distinct disease known as Chronic Traumatic Encephalopathy (CTE). The clinical manifestation of CTE is variable, but the symptoms of this progressive disease include impaired memory and cognition, affective disorders (i.e., impulsivity, aggression, depression, suicidality, etc.), and diminished motor control. Notably, mounting evidence suggests that the pathology contributing to CTE may be caused by repetitive exposure to subconcussive hits to the head, even in those with no history of a clinically evident head injury. Given the millions of athletes and military personnel with potential exposure to repetitive subconcussive insults and TBI, CTE represents an important public health issue. However, the incidence rates and pathological mechanisms are still largely unknown, primarily due to the fact that there is no in vivo diagnostic tool. The primary objective of this manuscript is to address this limitation and discuss potential neuroimaging modalities that may be capable of diagnosing CTE in vivo through the detection of tau and other known pathological features. Additionally, we will discuss the challenges of TBI research, outline the known pathology of CTE (with an emphasis on Tau), review current neuroimaging modalities to assess the potential routes for in vivo diagnosis, and discuss the future directions of CTE research.

Roles of CTCF and YY1 in T Cell Receptor Gene Rearrangement And T Cell Development

Diversity of T cell receptors (TCR) and immunoglobulins (Ig) is generated by V(D)J recombination of antigen receptor (AgR) loci. The Tcra-Tcrd locus is of particular interest because it displays a nested organization of Tcrd and Tcra gene segments and V(D)J recombination follows an intricate developmental program to assemble both TCRδ and TCRα repertoires. However, the mechanisms that dictate the developmental regulation of V(D)J recombination of the Tcra-Tcrd locus remain unclear.

We have previously shown that CCCTC-binding factor (CTCF) regulates Tcra gene transcription and rearrangement through organizing chromatin looping between CTCF- binding elements (CBEs). This study is one of many showing that CTCF functions as a chromatin organizer and transcriptional regulator genome-wide. However, detailed understanding of the impact of specific CBEs is needed to fully comprehend the biological function of CTCF and how CTCF influences the generation of the TCR repertoire during thymocyte development. Thus, we generated several mouse models with genetically modified CBEs to gain insight into the CTCF-dependent regulation of the Tcra-Tcrd locus. We revealed a CTCF-dependent chromatin interaction network at the Tcra-Tcrd locus in double-negative thymocytes. Disruption of a discrete chromatin loop encompassing Dδ, Jδ and Cδ gene segments allowed a single Vδ segment to frequently contact and rearrange to diversity and joining gene segments and dominate the adult TCRδ repertoire. Disruption of this loop also narrowed the TCRα repertoire, which, we believe, followed as a consequence of the restricted TCRδ repertoire. Hence, a single CTCF-mediated chromatin loop directly regulates TCRδ diversity and indirectly regulates TCRα diversity. In addition, we showed that insertion of an ectopic CBE can modify chromatin interactions and disrupt the rearrangement of particular Vδ gene segments. Finally, we investigated the role of YY1 in early T cell development by conditionally deleting YY1 in developing thymocytes. We found that early ablation of YY1 caused severe developmental defects in the DN compartment due to a dramatic increase in DN thymocyte apoptosis. Furthermore, late ablation of YY1 resulted in increased apoptosis of DP thymocytes and a restricted TCRα repertoire. Mechanistically, we showed that p53 was upregulated in both DN and DP YY1-deficient thymocytes. Eliminating p53 in YY1-deficient thymocytes rescued the survival and developmental defects, indicating that these YY1-dependent defects were p53-mediated. We conclude that YY1 is required to maintain cell viability during thymocyte development by thwarting the accumulation of p53.

Overall, this thesis work has shown that CTCF-dependent looping provides a central framework for lineage- and developmental stage-specific regulation of Tcra-Tcrd gene expression and rearrangements. In addition, we identified YY1 as a novel regulator of thymocyte viability.

Essays on Microeconometrics

My dissertation has three chapters which develop and apply microeconometric tech- niques to empirically relevant problems. All the chapters examines the robustness issues (e.g., measurement error and model misspecification) in the econometric anal- ysis. The first chapter studies the identifying power of an instrumental variable in the nonparametric heterogeneous treatment effect framework when a binary treat- ment variable is mismeasured and endogenous. I characterize the sharp identified set for the local average treatment effect under the following two assumptions: (1) the exclusion restriction of an instrument and (2) deterministic monotonicity of the true treatment variable in the instrument. The identification strategy allows for general measurement error. Notably, (i) the measurement error is nonclassical, (ii) it can be endogenous, and (iii) no assumptions are imposed on the marginal distribution of the measurement error, so that I do not need to assume the accuracy of the measure- ment. Based on the partial identification result, I provide a consistent confidence interval for the local average treatment effect with uniformly valid size control. I also show that the identification strategy can incorporate repeated measurements to narrow the identified set, even if the repeated measurements themselves are endoge- nous. Using the the National Longitudinal Study of the High School Class of 1972, I demonstrate that my new methodology can produce nontrivial bounds for the return to college attendance when attendance is mismeasured and endogenous.

The second chapter, which is a part of a coauthored project with Federico Bugni, considers the problem of inference in dynamic discrete choice problems when the structural model is locally misspecified. We consider two popular classes of estimators for dynamic discrete choice models: K-step maximum likelihood estimators (K-ML) and K-step minimum distance estimators (K-MD), where K denotes the number of policy iterations employed in the estimation problem. These estimator classes include popular estimators such as Rust (1987)’s nested fixed point estimator, Hotz and Miller (1993)’s conditional choice probability estimator, Aguirregabiria and Mira (2002)’s nested algorithm estimator, and Pesendorfer and Schmidt-Dengler (2008)’s least squares estimator. We derive and compare the asymptotic distributions of K- ML and K-MD estimators when the model is arbitrarily locally misspecified and we obtain three main results. In the absence of misspecification, Aguirregabiria and Mira (2002) show that all K-ML estimators are asymptotically equivalent regardless of the choice of K. Our first result shows that this finding extends to a locally misspecified model, regardless of the degree of local misspecification. As a second result, we show that an analogous result holds for all K-MD estimators, i.e., all K- MD estimator are asymptotically equivalent regardless of the choice of K. Our third and final result is to compare K-MD and K-ML estimators in terms of asymptotic mean squared error. Under local misspecification, the optimally weighted K-MD estimator depends on the unknown asymptotic bias and is no longer feasible. In turn, feasible K-MD estimators could have an asymptotic mean squared error that is higher or lower than that of the K-ML estimators. To demonstrate the relevance of our asymptotic analysis, we illustrate our findings using in a simulation exercise based on a misspecified version of Rust (1987) bus engine problem.

The last chapter investigates the causal effect of the Omnibus Budget Reconcil- iation Act of 1993, which caused the biggest change to the EITC in its history, on unemployment and labor force participation among single mothers. Unemployment and labor force participation are difficult to define for a few reasons, for example, be- cause of marginally attached workers. Instead of searching for the unique definition for each of these two concepts, this chapter bounds unemployment and labor force participation by observable variables and, as a result, considers various competing definitions of these two concepts simultaneously. This bounding strategy leads to partial identification of the treatment effect. The inference results depend on the construction of the bounds, but they imply positive effect on labor force participa- tion and negligible effect on unemployment. The results imply that the difference- in-difference result based on the BLS definition of unemployment can be misleading

due to misclassification of unemployment.