Choosing marginal or random-effects models for longitudinal binary responses: application to self-reported disability among older persons

BACKGROUND: Longitudinal studies with binary repeated outcomes are now widespread in epidemiology. The statistical analysis of these studies presents difficulties and standard methods are inadequate. METHODS: We consider strategies for modelling binary repeated responses and focus on two specific issues: the choice between marginal and random-effects models, and the choice of the time point origin. These issues are addressed using the example of self-reported disability in older women assessed annually for 6 years. The indicator of disability "needing help to go outdoors or home-confined" is used. RESULTS: In view of the observed associations between the responses for consecutive years, the baseline response was considered as a covariate. We compared the marginal and random-effects models first when only the influence of time and age is analysed and second when individual risk factors are studied in an aetiological perspective. There were substantial differences between the parameter estimates. They were due to differences between specific concepts related to the two models and the large between-individual heterogeneity revealed by the analysis. CONCLUSIONS: A random-effects model appears to be most suitable for the analysis of self-reported disability in older women

Guided Quasicontinuous Atom Laser

We report the first realization of a guided quasicontinuous atom laser by rf outcoupling a Bose-Einstein condensate from a hybrid optomagnetic trap into a horizontal atomic waveguide. This configuration allows us to cancel the acceleration due to gravity and keep the de Broglie wavelength constant at 0.5 $\mu$m during 0.1 s of propagation. We also show that our configuration, equivalent to pigtailing an optical fiber to a (photon) semiconductor laser, ensures an intrinsically good transverse mode matching.Comment: version published in Phys. Rev. Lett. 97, 200402 (2006

A quantum trampoline for ultra-cold atoms

We have observed the interferometric suspension of a free-falling Bose-Einstein condensate periodically submitted to multiple-order diffraction by a vertical 1D standing wave. The various diffracted matter waves recombine coherently, resulting in high contrast interference in the number of atoms detected at constant height. For long suspension times, multiple-wave interference is revealed through a sharpening of the fringes. We use this scheme to measure the acceleration of gravity

Targeted Learning of The Probability of Success of An In Vitro Fertilization Program Controlling for Time-dependent Confounders

Infertility is a global public health issue and various treatments are available. In vitro fertilization (IVF) is an increasingly common treatment method, but accurately assessing the success of IVF programs has proven challenging since they consist of multiple cycles. We present a double robust semiparametric method that incorporates machine learning to estimate the probability of success (i.e., delivery resulting from embryo transfer) of a program of at most four IVF cycles in the French Devenir Apr`es Interruption de la FIV (DAIFI) study and several simulation studies, controlling for time-dependent confounders. We find that the probability of success in the DAIFI study is 50% (95% confidence interval [0.48, 0.53]), therefore approximately half of future participants in a program of at most four IVF cycles can expect a delivery resulting from embryo transfer

Can atmospheric pollutants influence menstrual cycle function? Supplementary material

A few experimental studies suggest that atmospheric pollutants could affect the endocrine system, and in particular stress hormones and the hypothalamic-hypophyseal-ovarian axis, which could in turn influence menstrual cycle function. We aimed to study the possible short-term effects of atmospheric pollutants on the length of the follicular and luteal phases and on the duration of the menstrual cycle in humans. To do so, from a nation-wide study on couples' fecundity, we recruited 184 women not using contraception who collected urine samples at least every other day during one menstrual cycle, from which a progesterone metabolite was assayed, allowing estimation of the duration of the follicular and luteal phases of the cycle. Atmospheric pollution (nitrogen dioxide and particulate matter with an aerodynamical diameter below 10?m, PM10) levels were estimated from a dispersion model with a 1-km resolution combined with permanent monitoring stations measurements, allowing to estimate exposures in the 30-day, 1-10 and 11-30-day periods before the start of the menstrual cycle. Regression models allowed to quantify the change in cycle duration associated with atmospheric pollutants and adjusted for potential confounders. Follicular phase duration increased on average by 0.7 day (95% confidence interval, CI, 0.2; 1.3) for each increase by 10?g/m3 in NO2 concentration averaged over the 30 days before the cycle and by 1.6 day (95% CI, 0.3; 2.9) for each increase by 10?g/m3 in PM10. There was no strong evidence of associations of exposures in this time window with luteal phase or with total menstrual cycle durations (p>0.2). Exposures in the 1-10 day period before the cycle start were also associated with increased follicular phase duration. This study is one of the first prospective studies to suggest short-term alterations in follicular phase duration following atmospheric pollutants exposure