The measurement of low pay in the UK labour force survey

Consideration of the National Minimum Wage requires estimates of the distribution of hourly pay. The UK Labour Force Survey (LFS) is a key source of such estimates. The approach most frequently adopted by researchers has been to measure hourly earnings from several questions on pay and hours. The Office for National Statistics is now applying a new approach, based on an alternative more direct measurement introduced in March 1999. These two measures do not produce identical values and this paper investigates sources of discrepancies and concludes that the new variable is more accurate. The difficulty with using the new variable is that it is only available on a subset of respondents. An approach is developed in which missing values of the new variable are replaced by imputed values. The assumptions underlying this imputation approach and results of applying it to LFS data are presented. The relation to weighting approaches is also discussed

Outcome of adult patients with X-linked hypophosphatemia caused by PHEX gene mutations

X-linked hypophosphatemia (XLH) is the most common monogenic disorder causing hypophosphatemia. This case-note review documents the clinical features and the complications of treatment in 59 adults (19 male, 40 female) with XLH. XLH is associated with a large number of private mutations; 37 different mutations in the PHEX gene were identified in this cohort, 14 of which have not been previously reported. Orthopaedic involvement requiring surgical intervention (osteotomy) was frequent. Joint replacement and decompressive laminectomy were observed in those older than 40 years. Dental disease (63%), nephrocalcinosis (42%), and hearing impairment (14%) were also common. The rarity of the disease and the large number of variants make it difficult to discern specific genotype-phenotype relationships. A new treatment, an anti-FGF23 antibody, that may affect the natural history of the disease is currently being investigated in clinical trials

Should I stay or should I go? Sibling effects in household formation

This paper analyzes peer effects among siblings in the decision to leave parental home. Estimating peer effects is challenging because of problems of refection, endogenous group formation, and correlated unobservables. We overcome these issues using the exogenous variation in siblings' household formation implied by the eligibility rules for a Spanish rental subsidy. Our results show that sibling effects are negative and that these effects can be explained by the presence of old or ill parents. Sibling effects turn positive from older to younger close-in-age siblings, when imitation is more likely to prevail. Our findings indicate that policy makers who aim at fostering household formation should target the household rather than the individual and combine policies for young adults with policies for the elderly

Regression toward the mean – a detection method for unknown population mean based on Mee and Chua's algorithm

<p>Abstract</p> <p>Background</p> <p>Regression to the mean (RTM) occurs in situations of repeated measurements when extreme values are followed by measurements in the same subjects that are closer to the mean of the basic population. In uncontrolled studies such changes are likely to be interpreted as a real treatment effect.</p> <p>Methods</p> <p>Several statistical approaches have been developed to analyse such situations, including the algorithm of Mee and Chua which assumes a known population mean <it>μ</it>. We extend this approach to a situation where <it>μ </it>is unknown and suggest to vary it systematically over a range of reasonable values. Using differential calculus we provide formulas to estimate the range of <it>μ </it>where treatment effects are likely to occur when RTM is present.</p> <p>Results</p> <p>We successfully applied our method to three real world examples denoting situations when (a) no treatment effect can be confirmed regardless which <it>μ </it>is true, (b) when a treatment effect must be assumed independent from the true <it>μ </it>and (c) in the appraisal of results of uncontrolled studies.</p> <p>Conclusion</p> <p>Our method can be used to separate the wheat from the chaff in situations, when one has to interpret the results of uncontrolled studies. In meta-analysis, health-technology reports or systematic reviews this approach may be helpful to clarify the evidence given from uncontrolled observational studies.</p