A comparison of some confidence intervals for estimating the population coefficient of variation: a simulation study

This paper considers several confidence intervals for estimating the population coefficient of variation based on parametric, nonparametric and modified methods. A simulation study has been conducted to compare the performance of the existing and newly proposed interval estimators. Many intervals were modified in our study by estimating the variance with the median instead of the mean and these modifications were also successful. Data were generated from normal, chi-square, and gamma distributions for CV = 0.1, 0.3, and 0.5. We reported coverage probability and interval length for each estimator. The results were applied to two public health data: child birth weight and cigarette smoking prevalence. Overall, good intervals included an interval for chi-square distributions by McKay (1932), an interval estimator for normal distributions by Miller (1991), and our proposed interval

Accuracy and Precision of Insect Density and Impact Estimates

In estimating insect density and impact, entomologists are understandably interested in accuracy of estimation, but they almost always are dealing with precision because of bias due to an invalid estimator, probability sampling, or nonsampling errors. Definitions related to statistical estimation are reviewed and the concepts of accuracy and precision examined. Interval estimation and optimum sample size determination related to accuracy and precision, using the concept of allowable error, are examined. Criteria for selecting the best estimator in tenns of accuracy and precision are presented, and the distortion of probability statements due to bias is discussed. Accuracy and precision are compared and contrasted using two examples: (I) estimating insect density and (2) estimating insect impact. Adjusted and more accurate estimators can be obtained if the bias of an estimator can be estimated from a preliminary sample

On a Proper Meta-Analytic Model for Correlations

Combining statistical information across studies is a standard research tool in applied psychology. The most common approach in applied psychology is the fixed effects model. The fixed-effects approach assumes that individual study characteristics such as treatment conditions, study context, or individual differences do not influence study effect sizes. That is, that the majority of the differences between the effect sizes of different studies can be explained by sampling error alone. We critique the fixed-effects methodology for correlations and propose an advancement, the random-effects model, that ameliorates problems imposed by fixed-effects models. The random-effects approach explicitly incorporates between-study differences in data analysis and provides estimates of how those study characteristics influence the relationships among constructs of interest. Because they can model the influence of study characteristics, we assert that random-effects models have advantages for psychological research. Parameter estimates of both models are compared and evidence in favor of the random-effects approach is presented

Estimating regional unemployment with mobile network data for Functional Urban Areas in Germany

The ongoing growth of cities due to better job opportunities is leading to increased labour-relatedcommuter flows in several countries. On the one hand, an increasing number of people commuteand move to the cities, but on the other hand, the labour market indicates higher unemployment ratesin urban areas than in the surrounding areas. We investigate this phenomenon on regional level byan alternative definition of unemployment rates in which commuting behaviour is integrated. Wecombine data from the Labour Force Survey (LFS) with dynamic mobile network data by small areamodels for the federal state North Rhine-Westphalia in Germany. From a methodical perspective, weuse a transformed Fay-Herriot model with bias correction for the estimation of unemployment ratesand propose a parametric bootstrap for the Mean Squared Error (MSE) estimation that includes thebias correction. The performance of the proposed methodology is evaluated in a case study based onofficial data and in model-based simulations. The results in the application show that unemploymentrates (adjusted by commuters) in German cities are lower than traditional official unemployment ratesindicate

A systematic review of the role of bisphosphonates in metastatic disease

Objectives: To identify evidence for the role of bisphosphonates in malignancy for the treatment of hypercalcaemia, prevention of skeletal morbidity and use in the adjuvant setting. To perform an economic review of current literature and model the cost effectiveness of bisphosphonates in the treatment of hypercalcaemia and prevention of skeletal morbidity Data sources: Electronic databases (1966-June 2001). Cochrane register. Pharmaceutical companies. Experts in the field. Handsearching of abstracts and leading oncology journals (1999-2001). Review methods: Two independent reviewers assessed studies for inclusion, according to predetermined criteria, and extracted relevant data. Overall event rates were pooled in a meta-analysis, odds ratios ( OR) were given with 95% confidence intervals (CI). Where data could not be combined, studies were reported individually and proportions compared using chi- squared analysis. Cost and cost-effectiveness were assessed by a decision analytic model comparing different bisphosphonate regimens for the treatment of hypercalcaemia; Markov models were employed to evaluate the use of bisphosphonates to prevent skeletal-related events (SRE) in patients with breast cancer and multiple myeloma. Results: For acute hypercalcaemia of malignancy, bisphosphonates normalised serum calcium in >70% of patients within 2-6 days. Pamidronate was more effective than control, etidronate, mithramycin and low-dose clodronate, but equal to high dose clodronate, in achieving normocalcaemia. Pamidronate prolongs ( doubles) the median time to relapse compared with clodronate or etidronate. For prevention of skeletal morbidity, bisphosphonates compared with placebo, significantly reduced the OR for fractures (OR [95% CI], vertebral, 0.69 [0.57-0.84], non-vertebral, 0.65 [0.54-0.79], combined, 0.65 [0.55-0.78]) radiotherapy 0.67 [0.57-0.79] and hypercalcaemia 0.54 [0.36-0.81] but not orthopaedic surgery 0.70 [0.46-1.05] or spinal cord compression 0.71 [0.47-1.08]. However, reduction in orthopaedic surgery was significant in studies that lasted over a year 0.59 [0.39-0.88]. Bisphosphonates significantly increased the time to first SRE but did not affect survival. Subanalyses were performed for disease groups, drugs and route of administration. Most evidence supports the use of intravenous aminobisphosphonates. For adjuvant use of bisphosphonates, Clodronate, given to patients with primary operable breast cancer and no metastatic disease, significantly reduced the number of patients developing bone metastases. This benefit was not maintained once regular administration had been discontinued. Two trials reported significant survival advantages in the treated groups. Bisphosphonates reduce the number of bone metastases in patients with both early and advanced breast cancer. Bisphosphonates are well tolerated with a low incidence of side-effects. Economic modelling showed that for acute hypercalcaemia, drugs with the longest cumulative duration of normocalcaemia were most cost-effective. Zoledronate 4 mg was the most costly, but most cost-effective treatment. For skeletal morbidity, Markov models estimated that the overall cost of bisphosphonate therapy to prevent an SRE was pound250 and pound1500 per event for patients with breast cancer and multiple myeloma, respectively. Bisphosphonate treatment is sometimes cost-saving in breast cancer patients where fractures are prevented. Conclusions: High dose aminobisphosphonates are most effective for the treatment of acute hypercalcaemia and delay time to relapse. Bisphosphonates significantly reduce SREs and delay the time to first SRE in patients with bony metastatic disease but do not affect survival. Benefit is demonstrated after administration for at least 6-12 months. The greatest body of evidence supports the use of intravenous aminobisphosphonates. Further evidence is required to support use in the adjuvant setting

Estimating the size of dog populations in Tanzania to inform rabies control

Estimates of dog population sizes are a prerequisite for delivering effective canine rabies control. However, dog population sizes are generally unknown in most rabies-endemic areas. Several approaches have been used to estimate dog populations but without rigorous evaluation. We compare post-vaccination transects, household surveys, and school-based surveys to determine which most precisely estimates dog population sizes. These methods were implemented across 28 districts in southeast Tanzania, in conjunction with mass dog vaccinations, covering a range of settings, livelihoods, and religious backgrounds. Transects were the most precise method, revealing highly variable patterns of dog ownership, with human/dog ratios ranging from 12.4:1 to 181.3:1 across districts. Both household and school-based surveys generated imprecise and, sometimes, inaccurate estimates, due to small sample sizes in relation to the heterogeneity in patterns of dog ownership. Transect data were subsequently used to develop a predictive model for estimating dog populations in districts lacking transect data. We predicted a dog population of 2,316,000 (95% CI 1,573,000–3,122,000) in Tanzania and an average human/dog ratio of 20.7:1. Our modelling approach has the potential to be applied to predicting dog population sizes in other areas where mass dog vaccinations are planned, given census and livelihood data. Furthermore, we recommend post-vaccination transects as a rapid and effective method to refine dog population estimates across large geographic areas and to guide dog vaccination programmes in settings with mostly free roaming dog populations