Use of the bootstrap in analysing cost data from cluster randomised trials: some simulation results

BACKGROUND: This work has investigated under what conditions confidence intervals around the differences in mean costs from a cluster RCT are suitable for estimation using a commonly used cluster-adjusted bootstrap in preference to methods that utilise the Huber-White robust estimator of variance. The bootstrap's main advantage is in dealing with skewed data, which often characterise patient costs. However, it is insufficiently well recognised that one method of adjusting the bootstrap to deal with clustered data is only valid in large samples. In particular, the requirement that the number of clusters randomised should be large would not be satisfied in many cluster RCTs performed to date. METHODS: The performances of confidence intervals for simple differences in mean costs utilising a robust (cluster-adjusted) standard error and from two cluster-adjusted bootstrap procedures were compared in terms of confidence interval coverage in a large number of simulations. Parameters varied included the intracluster correlation coefficient, the sample size and the distributions used to generate the data. RESULTS: The bootstrap's advantage in dealing with skewed data was found to be outweighed by its poor confidence interval coverage when the number of clusters was at the level frequently found in cluster RCTs in practice. Simulations showed that confidence intervals based on robust methods of standard error estimation achieved coverage rates between 93.5% and 94.8% for a 95% nominal level whereas those for the bootstrap ranged between 86.4% and 93.8%. CONCLUSION: In general, 24 clusters per treatment arm is probably the minimum number for which one would even begin to consider the bootstrap in preference to traditional robust methods, for the parameter combinations investigated here. At least this number of clusters and extremely skewed data would be necessary for the bootstrap to be considered in favour of the robust method. There is a need for further investigation of more complex bootstrap procedures if economic data from cluster RCTs are to be analysed appropriately

Adolescent School Bullying Victimisation and Later Life Outcomes

We analyse the long-term effects of experiencing bullying victimisation in junior high school, using rich data on a large cohort of English adolescents. The data contain self-reports of five types of bullying and their frequency, for three waves, when the pupils were aged 13 to 16 years. We assess the effects of bullying victimisation on short- and long-term outcomes, including educational achievements, earnings, and mental ill-health at age 25 years using a variety of estimation strategies - least squares, matching, and inverse probability weighting. We also consider attenuation associated with relying on self-reports. The detailed longitudinal data, linked to administrative data, allows us to control for many of the determinants of child outcomes that have been explored in previous literature, together with comprehensive sensitivity analyses, to assess the potential role of unobserved variables. The pattern of results strongly suggests that there are quantitatively important long run effects on victims – stronger than correlation analysis would otherwise suggest. In particular, we find that both type of bullying and its intensity matters for long run outcomes such as obtaining a degree, income, and mental health

Parental separation and children’s education in a comparative perspective: Does the burden disappear when separation is more common?

Background: Parental breakup has, on average, a net negative effect on children's education. However, it is unclear whether this negative effect changes when parental separation becomes more common. Objective: We studied the variations in the effect of parental separation on children's chances of obtaining tertiary education across cohorts and countries with varying divorce rates. Methods: We applied country and cohort fixed-effect models as well as random-effect models to data from the first wave of the Generations and Gender Survey, complemented by selected macro-level indicators (divorce rate and educational expansion). Results: Country fixed-effect logistic regressions show that the negative effect of experiencing parental separation is stronger in more-recent birth cohorts. Random-intercept linear probability models confirm that the negative effect of parental breakup is significantly stronger when divorce is more common. Conclusions: The results support the low-conflict family dissolution hypothesis, which explains the trend by a rising proportion of low-conflict breakups. A child from a dissolving low-conflict family is likely to be negatively affected by family dissolution, whereas a child from a high-conflict dissolving family experiences relief. As divorce becomes more common and more low-conflict couples separate, more children are negatively affected, and hence, the average effect of breakup is more negative. Contribution: We show a significant variation in the size of the effect of parental separation on children's education; the effect becomes more negative when family dissolution is more common

Predictors of failed attendances in a multi-specialty outpatient centre using electronic databases.

BACKGROUND: Failure to keep outpatient medical appointments results in inefficiencies and costs. The objective of this study is to show the factors in an existing electronic database that affect failed appointments and to develop a predictive probability model to increase the effectiveness of interventions. METHODS: A retrospective study was conducted on outpatient clinic attendances at Tan Tock Seng Hospital, Singapore from 2000 to 2004. 22864 patients were randomly sampled for analysis. The outcome measure was failed outpatient appointments according to each patient's latest appointment. RESULTS: Failures comprised of 21% of all appointments and 39% when using the patients' latest appointment. Using odds ratios from the mutliple logistic regression analysis, age group (0.75 to 0.84 for groups above 40 years compared to below 20 years), race (1.48 for Malays, 1.61 for Indians compared to Chinese), days from scheduling to appointment (2.38 for more than 21 days compared to less than 7 days), previous failed appointments (1.79 for more than 60% failures and 4.38 for no previous appointments, compared with less than 20% failures), provision of cell phone number (0.10 for providing numbers compared to otherwise) and distance from hospital (1.14 for more than 14 km compared to less than 6 km) were significantly associated with failed appointments. The predicted probability model's diagnostic accuracy to predict failures is more than 80%. CONCLUSION: A few key variables have shown to adequately account for and predict failed appointments using existing electronic databases. These can be used to develop integrative technological solutions in the outpatient clinic

Inequality in Burkina Faso-to what extent do household, community and regional factors matter?

Empirical evidence suggests that regional disparities in income are often very wide, that these disparities do not necessarily disappear as economies grow and that these disparities are themselves a major driver of growth. We use a novel approach based on multilevel modelling to decompose the sources of inequality in household incomes in Burkina Faso. We show that differences in income across space are explained not only by the spatial concentration of households with favourable characteristics but to a large extent also by disparities in community endowments. Climatic differences across regions do matter, also, but to a much smaller extent. On the basis of the findings, it would be worth assessing the potential effects of policies which build and enhance infrastructure that connects communities complemented by interventions targeted to specific villages that particularly lag behind

Complex sample design effects and inference for mental health survey data

Mental health researchers world-wide are using large-scale sample survey methods to study mental health epidemiology and services utilization in general, non-clinical populations (Alegria et al. in press). This article reviews important statistical methods and software that apply to descriptive and multivariate analysis of data collected in sample surveys. A comparative analysis of mental health surveys in international locations is used to illustrate analysis procedures and ‘design effects’ for survey estimates of population statistics, model parameters and test statistics. This article addresses the following questions. How should a research analyst approach the analysis of sample survey data? Are there software tools available to perform this analysis? Is the use of ‘correct’ survey analysis methods important to interpretation of survey data? It addresses the question of approaches to the analysis of complex sample survey data. The latest developments in software tools for the analysis of complex sample survey data are covered, and empirical examples are presented that illustrate the impact of survey sample design features on the interpretation of confidence intervals and test statistics for univariate and multivariate analyses. Copyright © 1998 Whurr Publishers Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/35145/1/34_ftp.pd

Can the shadow economy undermine the effect of political stability on inflation? empirical evidence

This paper revisits the empirical relationship between political stability and inflation while explicitly accounting for the presence of the shadow economy. Using a large data set of 122 countries over the 1999 to 2007 period, we find that the well established negative correlation between political stability and inflation holds only if the size of the shadow economy remains modest; and it ceases to exist at higher levels of the size of the informal sector. This finding contributes to the existing literature on public finance that assigns special importance to political determinants of inflation. The results are robust against alternative specifications and satisfy the usual assumptions of a valid statistical inference

Eating Disorders Among a Community‐Based Sample of Chilean Female Adolescents

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/88044/1/jora733.pd

Facial width-to-height ratio relates to dominance style in the genus Macaca

Background. Physical, visual, chemical, and auditory cues signalling fighting ability have independently evolved in many animal taxa as a means to resolve conflicts without escalating to physical aggression. Facial width-to-height ratio (fWHR, i.e., the relative width to height of the face) has been associated with dominance-related phenotypes both in humans and in other primates. In humans, faces with a larger fWHR are perceived as more aggressive. Methods. We examined fWHR variation among 11 species of the genus Macaca. Macaques have been grouped into four distinct categories, from despotic to tolerant, based on their female dominance style. Female dominance style is related to intra and inter-sexual competition in both males and females and the result of different evolutionary pressure across species. We used female dominance style as a proxy of intra-/inter-sexual competition to test the occurrence of correlated evolution between competitive regimes and dominance-related phenotypes. fWHR was calculated from 145 2D-photographs of male and female adult macaques. Results. We found no phylogenetic signal on the differences in fWHR across species in the two sexes. However, fWHR was greater, in females and males, in species characterised by despotic female dominance style than in tolerant species. Discussion. Our results suggest that dominance-related phenotypes are related to differences in competitive regimes and intensity of inter- and intra-sexual selection across species

Analysis of dietary fibre of boiled and canned legumes commonly consumed in the United Kingdom

The use of different analytical methods to measure the dietary fibre content of foods complicates the interpretation of epidemiological studies. The aim of this study was to determine the total (TDF) and insoluble (IDF) fibre content of 14 boiled and canned legumes commonly consumed in the UK using the Association of Official Analytical Chemists (AOAC) enzymatic gravimetric method. The fibre values obtained were compared to non-starch polysaccharide (NSP) values. The results showed that mean values for TDF (2.7–11.2 g/100 g) were higher than NSP (2.6–6.7 g/100 g), with a mean NSP:TDF ratio of 1:1.43. TDF was correlated with NSP (r = 0.6; p = 0.02). Canning significantly reduced TDF and IDF by an average of 30% and 26% compared to boiling respectively. However, IDF represented at least 60% of the TDF in both boiled and canned samples. In conclusion, fibre values are affected by the processing and analytical method used