Design and analysis for three level hierarchical structures with count response

In numerous intervention studies and education field trials, random assignment to treatment occurs in clusters rather than at the level of observation. This departure of random assignment of units may be due to logistics, political feasibility, or ecological validity. Data within the same cluster or grouping are often correlated. Application of traditional regression techniques, which assume independence between observations, to clustered data produce consistent parameter estimates. However such estimators are often inefficient as compared to methods which incorporate the clustered nature of the data into the estimation procedure (Neuhaus 1993).1 Multilevel models, also known as random effects or random components models, can be used to account for the clustering of data by estimating higher level, or group, as well as lower level, or individual variation. Designing a study, in which the unit of observation is nested within higher level groupings, requires the determination of sample sizes at each level. This study investigates the design and analysis of various sampling strategies for a 3-level repeated measures design on the parameter estimates when the outcome variable of interest follows a Poisson distribution. ^ Results study suggest that second order PQL estimation produces the least biased estimates in the 3-level multilevel Poisson model followed by first order PQL and then second and first order MQL. The MQL estimates of both fixed and random parameters are generally satisfactory when the level 2 and level 3 variation is less than 0.10. However, as the higher level error variance increases, the MQL estimates become increasingly biased. If convergence of the estimation algorithm is not obtained by PQL procedure and higher level error variance is large, the estimates may be significantly biased. In this case bias correction techniques such as bootstrapping should be considered as an alternative procedure. For larger sample sizes, those structures with 20 or more units sampled at levels with normally distributed random errors produced more stable estimates with less sampling variance than structures with an increased number of level 1 units. For small sample sizes, sampling fewer units at the level with Poisson variation produces less sampling variation, however this criterion is no longer important when sample sizes are large. ^ 1Neuhaus J (1993). “Estimation efficiency and Tests of Covariate Effects with Clustered Binary Data”. Biometrics , 49, 989–996^

Descriptive epidemiology of cancer in three regions of Kazakhstan

The current study investigated data quality and estimated cancer incidence and mortality rates using data provided by Pavlodar, Semipalatinsk and Ust-Kamenogorsk Regional Cancer Registries of Kazakhstan during the period of 1996–1998. Assessment of data quality was performed using standard quality indicators including internal database checks, proportion of cases verified from death certificates only, mortality:incidence ratio, data patterns, proportion of cases with unknown primary site, proportion of cases with unknown age. Crude and age-adjusted incidence and mortality rates and 95% confidence intervals were calculated, by gender, for all cancers combined and for 28 specific cancer sites for each year of the study period. The five most frequent cancers were identified and described for every population. The results of the study provide the first simultaneous assessment of data quality and standardized incidence and mortality rates for Kazakh cancer registries. ^

An examination of the relationship between maternal and neighborhood-level characteristics and intrauterine growth retardation in Harris County, Texas, 1999--2001

The persistence of low birth weight and intrauterine growth retardation (IUGR) in the United States has puzzled researchers for decades. Much of the work that has been conducted on adverse birth outcomes has focused on low birth weight in general and not on IUGR. Studies that have examined IUGR specifically thus far have focused primarily on individual-level maternal risk factors. These risk factors have only been able to explain a small portion of the variance in IUGR. Therefore, recent work has begun to focus on community-level risk factors in addition to the individual-level maternal characteristics. This study uses Social Ecology to examine the relationship of individual and community-level risk factors and IUGR. Logistic regression was used to establish an individual-level model based on 155, 856 births recorded in Harris County, TX during 1999-2001. IUGR was characterized using a fetal growth ratio method with race/ethnic and sex specific mean birth weights calculated from national vital records. The spatial distributions of 114,460 birth records spatially located within the City of Houston were examined using choropleth, probability and density maps. Census tracts with higher than expected rates of IUGR and high levels of neighborhood disadvantage were highlighted. Neighborhood disadvantage was constructed using socioeconomic variables from the 2000 U.S. Census. Factor analysis was used to create a unified single measure. Lastly, a random coefficients model was used to examine the relationship between varying levels of community disadvantage, given the set of individual-level risk factors for 152,997 birth records spatially located within Harris County, TX. Neighborhood disadvantage was measured using three different indices adapted from previous work. The findings show that pregnancy-induced hypertension, previous preterm infant, tobacco use and insufficient weight gain have the highest association with IUGR. Neighborhood disadvantage only slightly further increases the risk of IUGR (OR 1.12 to 1.23). Although community level disadvantage only helped to explain a small proportion of the variance of IUGR, it did have a significant impact. This finding suggests that community level risk factors should be included in future work with IUGR and that more work needs to be conducted. ^

Trends in utilization of computer tomography (CT) scans for victims of motor vehicle collision (MVCs) in a level I trauma center from 1996 to 2006

Purpose. To evaluate trends in the utilization of head, abdominal, thoracic and other body regions CTs in the management of victims of MVC at a level I trauma center from 1996 to 2006.^ Method. From the trauma registry, I identified patients involved in MVC's in a level I trauma center and categorized them into three age groups of 13-18, 19-55 and ≥56. I used International Classification of Disease (ICD-9-CM) codes to find the type and number of CTs examinations performed for each patient. I plotted the mean number of CTs per patient against year of admission to find the crude estimate of change in utilization pattern for each type of CT. I used logistic regression to assess whether repetitive CTs (≥ 2) for head, abdomen, thorax and other body regions were associated with age group and year of admission for MVC patients. I adjusted the estimates for gender, ethnicity, insurance status, mechanism and severity of injury, intensive care unit admission status, patient disposition (dead or alive) and year of admission.^ Results. Utilization of head, abdominal, thoracic and other body regions CTs significantly increased over 11-year period. Utilization of head CT was greatest in the 13-18 age group, and increased from 0.58 CT/patient in 1996 to 1.37 CT/patient in 2006. Abdominal CTs were more common in the ≥56+ age group, and increased from 0.33 CT/patient in 1996 to 0.72 CT/patient in 2006. Utilization of thoracic CTs was higher in the 56+ age group, and increased from 0.01 CT/patient in 1996 to 0.42 CT/patient in 2006. Utilization of other CTs did not change materially during the study period for adolescents, adults or older adults. In the multivariable analysis, after adjustment for potential confounders, repetitive head CTs significantly increased in the 13-18 age group (95% CI: 1.29-1.87, p=<0.001) relative to the 19-55 age group. Repetitive thoracic CT use was lower in adolescents (95% CI: 0.22-0.70, p=<0.001) relative to the 19-55 age group.^ Conclusion. There has been a substantial increase in the utilization of head, abdominal, thoracic and other CTs in the management of MVC patients. Future studies need to identify if increased utilization of CTs have resulted in better health outcome for these patients. ^