Regression Models for Adjusting the 1980 Census

A Debate on Adjusting the Census for Undercount

Adjusting U.S. Census TIGER/Line Blocks

The Census employs a crude level of spatial accuracy and detail in the creation of TIGER/Line data. This level is sufficient for the collection of the census and to allow demographic GIS analysis of the data. Consequently TIGER/Line data cannot be overlayed with more accurate data. This paper presents County of Contra Costa Community Development Department to recreation of TIGER blocks using ou...

Adjusting for regression effect in uncontrolled studies.

When clinical studies require enrolled patients to have abnormal assays, the natural tendency of repeat measurements to regress toward the mean can lead to a false assessment of effectiveness of therapy. We propose a method to more accurately estimate the true effect of therapy by adjusting for a component of improvement that can be attributed to regression effect. The model we use allows for a...

the application of multivariate probit models for conditional claim-types (the case study of iranian car insurance industry)

هدف اصلی نرخ گذاری بیمه ای تعیین نرخ عادلانه و منطقی از دیدگاه بیمه گر و بیمه گذار است. تعین نرخ یکی از مهم ترین مسایلی است که شرکتهای بیمه با آن روبرو هستند، زیرا تعیین نرخ اصلی ترین عامل در رقابت بین شرکتها است. برای تعیین حق بیمه ابتدا می باید مقدار مورد انتظار ادعای خسارت برای هر قرارداد بیمه را برآورد کرد. روش عمومی مدل سازی خسارتهای عملیاتی در نظر گرفتن تواتر و شدت خسارتها می باشد. اگر شر...

Adjusting for Confounding in Early Postlaunch Settings: Going Beyond Logistic Regression Models.

BACKGROUND Postlaunch data on medical treatments can be analyzed to explore adverse events or relative effectiveness in real-life settings. These analyses are often complicated by the number of potential confounders and the possibility of model misspecification. METHODS We conducted a simulation study to compare the performance of logistic regression, propensity score, disease risk score, and...