Confidence Intervals for the Mean of a Poisson Distribution: A Review

Sahai, Hardeo; Khurshid, Anwer

doi:10.1002/bimj.4710350716

Cited by 123 publications

(89 citation statements)

References 13 publications

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“…Breast cancer is the most common cancer among Icelandic women, with an age standardized incidence of 90.4 per 100 000 person years in the period 2001Á2005, a level similar to that in other Nordic countries [10,11]. According to our results, Icelandic women with academic education had 25% higher incidence of breast cancer than women with basic education only.…”

Section: Discussionsupporting

confidence: 80%

“…The age-standardized (world standard) incidence per 100 000 person years was 91.4 in the period of 2001Á2005 and is currently the highest in the Nordic countries [10,11]. The findings of a higher risk of prostate cancer associated with higher education are in accordance with results from other Nordic countries.…”

Section: Discussionsupporting

confidence: 68%

“…Standardized incidence ratios (SIRs) for each educational group were calculated as ratios of observed number of cancer cases to those expected from the national cancer incidence rates, by sex, 5-year birth cohorts and 1-year calendar periods [9]. The 95% confidence intervals (CIs) for the SIRs were calculated by method of Sahai and Khursid [10]. The test for trend over educational categories was based on the method of Breslow and Day [9].…”

Section: Methodsmentioning

confidence: 99%

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Cancer risk by education in Iceland; a census-based cohort study

et al. 2008

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Section: Discussionsupporting

confidence: 80%

Section: Discussionsupporting

confidence: 68%

Section: Methodsmentioning

confidence: 99%

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Cancer risk by education in Iceland; a census-based cohort study

et al. 2008

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“…Because of low first year observed referrals (approximately 75% of facilities had ,15 referrals), exact 95% confidence intervals (95% CIs) were calculated for observed referrals and divided by the expected referrals to obtain the exact 95% CI of STReR (17). Patients with missing data were not excluded from the STReR calculation.…”

Section: Strer and 95% Confidence Intervalsmentioning

confidence: 99%

Standardized Transplantation Referral Ratio to Assess Performance of Transplant Referral among Dialysis Facilities

Paul

Plantinga

Pastan

et al. 2018

CJASN

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Background and objectives For patients with ESRD, referral from a dialysis facility to a transplant center for evaluation is an important step toward kidney transplantation. However, a standardized measure for assessing clinical performance of dialysis facilities transplant access is lacking. We describe methodology for a new dialysis facility measure: the Standardized Transplantation Referral Ratio.Design, setting, participants, & measurements Transplant referral data from 8308 patients with incident ESRD within 249 dialysis facilities in the United States state of Georgia were linked with US Renal Data System data from January of 2008 to December of 2011, with follow-up through December of 2012. Facility-level expected referrals were computed from a two-stage Cox proportional hazards model after patient case mix risk adjustment including demographics and comorbidities. The Standardized Transplantation Referral Ratio (95% confidence interval) was calculated as a ratio of observed to expected referrals. Measure validity and reliability were assessed.Results Over 2008-2011, facility Standardized Transplantation Referral Ratios in Georgia ranged from 0 to 4.87 (mean =1.16, SD=0.76). Most (77%) facilities had observed referrals as expected, whereas 11% and 12% had Standardized Transplantation Referral Ratios significantly greater than and less than expected, respectively. Age, race, sex, and comorbid conditions were significantly associated with the likelihood of referral, and they were included in risk adjustment for Standardized Transplantation Referral Ratio calculations. The Standardized Transplantation Referral Ratios were positively associated with evaluation, waitlisting, and transplantation (r=0.46, 0.35, and 0.20, respectively; P,0.01). On average, approximately 33% of the variability in Standardized Transplantation Referral Ratios was attributed to between-facility variation, and 67% of the variability in Standardized Transplantation Referral Ratios was attributed to within-facility variation.Conclusions The majority of observed variation in dialysis facility referral performance was due to characteristics within a dialysis facility rather than patient factors included in risk adjustment models. Our study shows a method for computing a facility-level standardized measure for transplant referral on the basis of a pilot sample of Georgia dialysis facilities that could be used to monitor transplant referral performance of dialysis facilities.

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“…Incident rate ratios (IRR) were computed for the outcome measure with 95% CI (Sahai and Khurshid, 1993). With patient data nested within local government districts, we used a two-level, mixed-effects, multivariable Poisson regression (patients, level 1: fixed; area, level 2: random) to model the association of patient and treatment covariates on outcome (Stata procedure: meqrpoisson).…”

Section: Post-admission Offendingmentioning

confidence: 99%