Poisson regression analysis of ungrouped data.

نویسندگان

  • D Loomis
  • D B Richardson
  • L Elliott
چکیده

BACKGROUND Poisson regression is routinely used for analysis of epidemiological data from studies of large occupational cohorts. It is typically implemented as a grouped method of data analysis in which all exposure and covariate information is categorised and person-time and events are tabulated. AIMS To describe an alternative approach to Poisson regression analysis using single units of person-time without grouping. METHODS Data for simulated and empirical cohorts were analysed by Poisson regression. In analyses of simulated data, effect estimates derived via Poisson regression without grouping were compared to those obtained under proportional hazards regression. Analyses of empirical data for a cohort of 138 900 electrical workers were used to illustrate how the ungrouped approach may be applied in analyses of actual occupational cohorts. RESULTS Using simulated data, Poisson regression analyses of ungrouped person-time data yield results equivalent to those obtained via proportional hazards regression: the results of both methods gave unbiased estimates of the "true" association specified for the simulation. Analyses of empirical data confirm that grouped and ungrouped analyses provide identical results when the same models are specified. However, bias may arise when exposure-response trends are estimated via Poisson regression analyses in which exposure scores, such as category means or midpoints, are assigned to grouped data. CONCLUSIONS Poisson regression analysis of ungrouped person-time data is a useful tool that can avoid bias associated with categorising exposure data and assigning exposure scores, and facilitate direct assessment of the consequences of exposure categorisation and score assignment on regression results.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Hurdle, Inflated Poisson and Inflated Negative Binomial Regression Models ‎ for Analysis of Count Data with Extra Zeros

In this paper‎, ‎we ‎propose ‎Hurdle regression models for analysing count responses with extra zeros‎. A method of estimating maximum likelihood is used to estimate model parameters. The application of the proposed model is presented in insurance dataset‎. In this example‎, there are many numbers of claims equal to zero is considered that clarify the application of the model with a zero-inflat...

متن کامل

کاربرد مدل رگرسیون پواسنی تعمیم یافته در تحلیل داده‌های باروری زنان روستایی استان فارس

Background & objectives: statistical modeling explicates the observed changes in data by means of mathematics equations. In cases that dependent variable is count, Poisson model is applied. If Poisson model is not applicable in a specific situation, it is better to apply the generalized Poisson model. So, our emphasis in this study is to notice the data structure, introducing the generalized Po...

متن کامل

Comparison between Efficiency of Poisson Regression Model and Negative Binomial Regression in the Analysis of Factors Affecting Mortality from Cardiovascular Diseases in Yazd Province in 2017

      Introduction: Despite the advances in cardiovascular diseases, death caused by these diseases is still considered as the leading cause of mortality. In this study, some of the effective factors on the deaths caused by cardiovascular diseases were investigated Methods: This cross-sectional analytical study investigated the efficacy of Poisson regression models and negative binomial regres...

متن کامل

Jackknifed Liu-type Estimator in Poisson Regression Model

The Liu estimator has consistently been demonstrated to be an attractive shrinkage method for reducing the effects of multicollinearity. The Poisson regression model is a well-known model in applications when the response variable consists of count data. However, it is known that multicollinearity negatively affects the variance of the maximum likelihood estimator (MLE) of the Poisson regressio...

متن کامل

P-66: There Is No Difference between IVF/ICSI Cycle Outcome in Patients With and without PCOS; A Modified Poisson Regression Model

Background Polycystic ovary syndrome is a frequent condition in women of reproductive age with prevalence rate of 5-10%. This study purposed to determine the relationship between polycystic ovary syndrome and the outcome of assisted reproductive treatment (ART) cycle in Tehran, Iran. MaterialsAndMethods In this historical cohort study, 996 infertile women who were referred to Royan Institute (T...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Occupational and environmental medicine

دوره 62 5  شماره 

صفحات  -

تاریخ انتشار 2005