A cautionary note regarding count models of alcohol consumption in randomized controlled trials

BACKGROUND: Alcohol consumption is commonly used as a primary outcome in randomized alcohol treatment studies. The distribution of alcohol consumption is highly skewed, particularly in subjects with alcohol dependence. METHODS: In this paper, we will consider the use of count models for outcomes in a randomized clinical trial setting. These include the Poisson, over-dispersed Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial. We compare the Type-I error rate of these methods in a series of simulation studies of a randomized clinical trial, and apply the methods to the ASAP (Addressing the Spectrum of Alcohol Problems) trial. RESULTS: Standard Poisson models provide a poor fit for alcohol consumption data from our motivating example, and did not preserve Type-I error rates for the randomized group comparison when the true distribution was over-dispersed Poisson. For the ASAP trial, where the distribution of alcohol consumption featured extensive over-dispersion, there was little indication of significant randomization group differences, except when the standard Poisson model was fit. CONCLUSION: As with any analysis, it is important to choose appropriate statistical models. In simulation studies and in the motivating example, the standard Poisson was not robust when fit to over-dispersed count data, and did not maintain the appropriate Type-I error rate. To appropriately model alcohol consumption, more flexible count models should be routinely employed

The impact of attrition on the representativeness of cohort studies of older people

Background: There are well-established risk factors, such as lower education, for attrition of study participants. Consequently, the representativeness of the cohort in a longitudinal study may deteriorate over time. Death is a common form of attrition in cohort studies of older people. The aim of this paper is to examine the effects of death and other forms of attrition on risk factor prevalence in the study cohort and the target population over time

Observed intra-cluster correlation coefficients in a cluster survey sample of patient encounters in general practice in Australia

BACKGROUND: Cluster sample study designs are cost effective, however cluster samples violate the simple random sample assumption of independence of observations. Failure to account for the intra-cluster correlation of observations when sampling through clusters may lead to an under-powered study. Researchers therefore need estimates of intra-cluster correlation for a range of outcomes to calculate sample size. We report intra-cluster correlation coefficients observed within a large-scale cross-sectional study of general practice in Australia, where the general practitioner (GP) was the primary sampling unit and the patient encounter was the unit of inference. METHODS: Each year the Bettering the Evaluation and Care of Health (BEACH) study recruits a random sample of approximately 1,000 GPs across Australia. Each GP completes details of 100 consecutive patient encounters. Intra-cluster correlation coefficients were estimated for patient demographics, morbidity managed and treatments received. Intra-cluster correlation coefficients were estimated for descriptive outcomes and for associations between outcomes and predictors and were compared across two independent samples of GPs drawn three years apart. RESULTS: Between April 1999 and March 2000, a random sample of 1,047 Australian general practitioners recorded details of 104,700 patient encounters. Intra-cluster correlation coefficients for patient demographics ranged from 0.055 for patient sex to 0.451 for language spoken at home. Intra-cluster correlations for morbidity variables ranged from 0.005 for the management of eye problems to 0.059 for management of psychological problems. Intra-cluster correlation for the association between two variables was smaller than the descriptive intra-cluster correlation of each variable. When compared with the April 2002 to March 2003 sample (1,008 GPs) the estimated intra-cluster correlation coefficients were found to be consistent across samples. CONCLUSIONS: The demonstrated precision and reliability of the estimated intra-cluster correlations indicate that these coefficients will be useful for calculating sample sizes in future general practice surveys that use the GP as the primary sampling unit

Factors affecting study efficiency and item non-response in health surveys in developing countries: the Jamaica national healthy lifestyle survey

BACKGROUND: Health surveys provide important information on the burden and secular trends of risk factors and disease. Several factors including survey and item non-response can affect data quality. There are few reports on efficiency, validity and the impact of item non-response, from developing countries. This report examines factors associated with item non-response and study efficiency in a national health survey in a developing Caribbean island. METHODS: A national sample of participants aged 15–74 years was selected in a multi-stage sampling design accounting for 4 health regions and 14 parishes using enumeration districts as primary sampling units. Means and proportions of the variables of interest were compared between various categories. Non-response was defined as failure to provide an analyzable response. Linear and logistic regression models accounting for sample design and post-stratification weighting were used to identify independent correlates of recruitment efficiency and item non-response. RESULTS: We recruited 2012 15–74 year-olds (66.2% females) at a response rate of 87.6% with significant variation between regions (80.9% to 97.6%; p < 0.0001). Females outnumbered males in all parishes. The majority of subjects were recruited in a single visit, 39.1% required multiple visits varying significantly by region (27.0% to 49.8% [p < 0.0001]). Average interview time was 44.3 minutes with no variation between health regions, urban-rural residence, educational level, gender and SES; but increased significantly with older age category from 42.9 minutes in the youngest to 46.0 minutes in the oldest age category. Between 15.8% and 26.8% of persons did not provide responses for the number of sexual partners in the last year. Women and urban residents provided less data than their counterparts. Highest item non-response related to income at 30% with no gender difference but independently related to educational level, employment status, age group and health region. Characteristics of non-responders vary with types of questions. CONCLUSION: Informative health surveys are possible in developing countries. While survey response rates may be satisfactory, item non-response was high in respect of income and sexual practice. In contrast to developed countries, non-response to questions on income is higher and has different correlates. These findings can inform future surveys

Radiosensitivity of murine and human melanoma cells: a comparative study with different models.

The in vitro radiosensitivity of one murine melanoma cell line (Cloudman S91 CCL 53.1) and three human melanoma cell strains (C8146C, C8161, and R83-4) were studied. Cells were irradiated by single dose X-rays and plated either in agar or on plastic. The survival curves were fitted by the single-hit multitarget, two-hit multitarget, and quadratic models. Multiple comparisons of the residual sum of squares suggested that the two-hit model was clearly inferior to the single-hit and quadratic models. No statistically significant difference was suggested for either the single-hit or quadratic models. Furthermore, on examination of the differences in correlations between the observed and predicted values, the residual plots (observed minus predicted over dose) failed to suggest a clear advantage of either the single-hit multitarget or the quadratic models. Either model could be recommended for analysis of in vitro radiation data

Radiosensitivity of murine and human melanoma cells: a comparative study with different models.

The in vitro radiosensitivity of one murine melanoma cell line (Cloudman S91 CCL 53.1) and three human melanoma cell strains (C8146C, C8161, and R83-4) were studied. Cells were irradiated by single dose X-rays and plated either in agar or on plastic. The survival curves were fitted by the single-hit multitarget, two-hit multitarget, and quadratic models. Multiple comparisons of the residual sum of squares suggested that the two-hit model was clearly inferior to the single-hit and quadratic models. No statistically significant difference was suggested for either the single-hit or quadratic models. Furthermore, on examination of the differences in correlations between the observed and predicted values, the residual plots (observed minus predicted over dose) failed to suggest a clear advantage of either the single-hit multitarget or the quadratic models. Either model could be recommended for analysis of in vitro radiation data