Article

Confidence limits made easy: interval estimation using a substitution method.

Department of Public Health Medicine and Epidemiology, University College Dublin, Ireland.
American Journal of Epidemiology (Impact Factor: 4.78). 04/1998; 147(8):783-90.
Source: PubMed

ABSTRACT The use of confidence intervals has become standard in the presentation of statistical results in medical journals. Calculation of confidence limits can be straightforward using the normal approximation with an estimate of the standard error, and in particular cases exact solutions can be obtained from published tables. However, for a number of commonly used measures in epidemiology and clinical research, formulae either are not available or are so complex that calculation is tedious. The author describes how an approach to confidence interval estimation which has been used in certain specific instances can be generalized to obtain a simple and easily understood method that has wide applicability. The technique is applicable as long as the measure for which a confidence interval is required can be expressed as a monotonic function of a single parameter for which the confidence limits are available. These known confidence limits are substituted into the expression for the measure--giving the required interval. This approach makes fewer distributional assumptions than the use of the normal approximation and can be more accurate. The author illustrates his technique by calculating confidence intervals for Levin's attributable risk, some measures in population genetics, and the "number needed to be treated" in a clinical trial. Hitherto the calculation of confidence intervals for these measures was quite problematic. The substitution method can provide a practical alternative to the use of complex formulae when performing interval estimation, and even in simpler situations it has major advantages.

0 Bookmarks
 · 
132 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Several studies have demonstrated the effects of health behaviours on risk of chronic diseases and mortality, but none have investigated their contribution to potentially preventable hospitalisation (PPH). We aimed to quantify the effects on risk of PPH of six health behaviours: smoking; alcohol consumption; physical activity; fruit and vegetables consumption; sitting time; and sleeping time. Prospective observational study in New South Wales, Australia. 267,006 men and women aged 45 years and over. PPH admissions and mortality during follow-up according to individual positive health behaviours (non-smoking, <14 alcoholic drinks per week, ≥2.5 hours of physical activity per week, ≥2 servings of fruit and 5 servings of vegetables per day, <8 hours sitting and ≥7 hours sleeping per day) and the total number of these behaviours. During an average of 3 years follow-up, 20971 (8%) participants had at least one PPH admission. After adjusting for potential confounders, participants who reported all six positive health behaviours at baseline had 46% lower risk of PPH admission (95% CI 0.48-0.61), compared to those who reported having only one of these behaviours. Based on these risk estimates, approximately 29% of PPH admissions in Australians aged 45 years and over were attributable to not adhering to the six health behaviours. Estimates were similar for acute, chronic and vaccine-preventable categories of PPH admissions. Individual and combined positive health behaviours were associated with lower risk of PPH admission. These findings suggest that there is a significant opportunity to reduce PPH by promoting healthy behaviours.
    PLoS ONE 01/2014; 9(4):e93111. · 3.73 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Hurling is a stick handling game which, although native to Ireland, has international reach and presence. The aim of this study was to report incidence and type of injuries incurred by elite male hurling players over five consecutive playing seasons.
    BMJ Open 01/2014; 4(6):e005059. · 1.58 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Background. To test the hypothesis that cognitive impairment in older adults is associated with all-cause mortality risk and the risk increases when the degree of cognitive impairment augments; and then, if this association is confirmed, to report the population-attributable fraction (PAF) of mortality due to cognitive impairment. Method. A representative random community sample of individuals aged over 55 was interviewed, and 4557 subjects remaining alive at the end of the first year of follow-up were included in the analysis. Instruments used in the assessment included the Mini-Mental Status Examination (MMSE), the History and Aetiology Schedule (HAS) and the Geriatric Mental State (GMS)-AGECAT. For the standardised degree of cognitive impairment Perneczky et al's MMSE criteria were applied. Mortality information was obtained from the official population registry. Multivariate Cox proportional hazard models were used to test the association between MMSE degrees of cognitive impairment and mortality risk. We also estimated the PAF of mortality due to specific MMSE stages. Results. Cognitive impairment was associated with mortality risk, the risk increasing in parallel with the degree of cognitive impairment (Hazard ratio, HR: 1.18 in the 'mild' degree of impairment; HR: 1.29 in the 'moderate' degree; and HR: 2.08 in the 'severe' degree). The PAF of mortality due to severe cognitive impairment was 3.49%. Conclusions. A gradient of increased mortality-risk associated with severity of cognitive impairment was observed. The results support the claim that routine assessment of cognitive function in older adults should be considered in clinical practice.
    Epidemiology and Psychiatric Sciences 06/2014; · 2.94 Impact Factor

Full-text

View
3 Downloads
Available from