Violence against primary school children with disabilities in Uganda: a cross-sectional study.

BACKGROUND: 150 million children live with disabilities globally, and a recent systematic review found 3 to 4 times the levels of violence versus non-disabled children in high income countries. However, almost nothing is known about violence against disabled children in lower income countries. We aim to explore the prevalence, patterns and risk factors for physical, sexual and emotional violence among disabled children attending primary school in Luwero District, Uganda. METHODS: We performed a secondary analysis of data from the baseline survey of the Good Schools Study. 3706 children and young adolescents aged 11-14 were randomly sampled from 42 primary schools. Descriptive statistics were computed and logistic regression models fitted. RESULTS: 8.8% of boys and 7.6% of girls reported a disability. Levels of violence against both disabled and non-disabled children were extremely high. Disabled girls report slightly more physical (99.1% vs 94.6%, p = 0.010) and considerably more sexual violence (23.6% vs 12.3%, p = 0.002) than non-disabled girls; for disabled and non-disabled boys, levels are not statistically different. The school environment is one of the main venues at which violence is occurring, but patterns differ by sex. Risk factors for violence are similar between disabled and non-disabled students. CONCLUSIONS: In Uganda, disabled girls are at particular risk of violence, notably sexual violence. Schools may be a promising venue for intervention delivery. Further research on the epidemiology and prevention of violence against disabled and non-disabled children in low income countries is urgently needed

Robust linear regression in replicated measurement error models

We propose robust and bounded influence methods for linear regression when some of the predictors are measured with error. We address the important special case that the surrogate predictors are replicated, and that the measurement errors in response and predictors are correlated. The robust methods proposed are variants of the so-called Mallows class of estimates. The resulting estimators are easily computed and have a simple asymptotic theory. An example is used to illustrate the results.Asymptotic theory bounded influence estimators errors in variables leverage Mallows estimates

An Economist's Primer on Survey Samples

Survey data underlie most empirical work in economics, yet economists typically have little familiarity with survey sample design and its effects on inference. This paper describes how sample designs depart from the simple random sampling model implicit in most econometrics textbooks, points out where the effects of this departure are likely to be greatest, and describes the relationship between design-based estimators developed by survey statisticians and related econometric methods for regression. Its intent is to provide empirical economists with enough background in survey methods to make informed use of design-based estimators. It emphasizes surveys of households (the source of most public-use files), but also considers how surveys of businesses differ. Examples from the National Longitudinal Survey of Youth of 1979 and the Current Population Survey illustrate practical aspects of design-based estimation.CES,economic,research,micro,data,microdata,chief,economist

The new strategy for the concise presentation of sampling errors in the Italian Structural Business Statistics Survey

Generalized variance functions, Design effect, Business survey,