A Scaled Linear Mixed Model for Multiple Outcomes

We propose a scaled linear mixed model to assess the effects of exposure and other covariates on multiple continuous outcomes. The most general form of the model allows a different exposure effect for each outcome. An important special case is a model that represents the exposure effects using a common global measure that can be characterized in terms of effect sizes. Correlations among different outcomes within the same subject are accommodated using random effects. We develop two approaches to model fitting, including the maximum likelihood method and the working parameter method. A key feature of both methods is that they can be easily implemented by repeatedly calling software for fitting standard linear mixed models, e.g., SAS PROC MIXED. Compared to the maximum likelihood method, the working parameter method is easier to implement and yields fully efficient estimators of the parameters of interest. We illustrate the proposed methods by analyzing data from a study of the effects of occupational pesticide exposure on semen quality in a cohort of Chinese men.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66256/1/j.0006-341X.2000.00593.x.pd

Management of early pregnancy loss with mifepristone and misoprostol: clinical predictors of treatment success from a randomized trial.

BackgroundEarly pregnancy loss is a common event in the first trimester, occurring in 15%-20% of confirmed pregnancies. A common evidence-based medical regimen for early pregnancy loss uses misoprostol, a prostaglandin E1 analog, with a dosage of 800 μg, self-administered vaginally. The clinical utility of this regimen is limited by suboptimal effectiveness in patients with a closed cervical os, with 29% of patients experiencing early pregnancy loss requiring a second dose after 3 days and 16% of patients eventually requiring a uterine aspiration procedure.ObjectiveThis study aimed to evaluate clinical predictors associated with treatment success in patients receiving medical management with mifepristone-misoprostol or misoprostol alone for early pregnancy loss.Study designWe performed a planned secondary analysis of a randomized trial comparing mifepristone-misoprostol with misoprostol alone for management of early pregnancy loss. The published prediction model for treatment success of single-dose misoprostol administered vaginally included the following variables: active bleeding, type of early pregnancy loss (anembryonic pregnancy or embryonic and/or fetal demise), parity, gestational age, and treatment site; previous significant predictors were vaginal bleeding within the past 24 hours and parity of 0 or 1 vs >1. To determine if these characteristics predicted differential proportions of patients with treatment success or failure, we performed bivariate analyses; given the small proportion of treatment failures in the combined treatment arm, both arms were combined for analysis. Thereafter, we performed a logistic regression analysis to assess the effect of these predictors collectively in each of the 2 treatment groups separately as well as in the full cohort as a proxy for the combined treatment arm. Finally, by using receiver operating characteristic curves, we tested the ability of these predictors in association with misoprostol treatment success to discriminate between treatment success and treatment failure. To quantify the ability of the score to discriminate between treatment success and treatment failure in each treatment arm as well as in the entire cohort, we calculated the area under the curve. Using multivariable logistic regression, we then assessed our study population for other predictors of treatment success in both treatment groups, with and without mifepristone pretreatment.ResultsOverall, 297 evaluable participants were included in the primary study, with 148 in the mifepristone-misoprostol combined treatment group and 149 in the misoprostol-alone treatment group. Among patients who had vaginal bleeding at the time of treatment, 15 of 17 (88%) in the mifepristone-misoprostol combined treatment group and 12 of 17 (71%) in the misoprostol-alone treatment group experienced expulsion of pregnancy tissue. Among patients with a parity of 0 or 1, 94 of 108 (87%) in the mifepristone-misoprostol treatment group and 66 of 95 (69%) in the misoprostol-alone treatment group experienced expulsion of pregnancy tissue. These clinical characteristics did not predict treatment success in the combined cohort alone (area under the curve=0.56; 95% confidence interval, 0.48-0.64). No other baseline clinical factors predicted treatment success in the misoprostol-alone treatment arm or mifepristone pretreatment arm. In the full cohort, the significant predictors of treatment success were pretreatment with mifepristone (adjusted odds ratio=2.51; 95% confidence interval, 1.43-4.43) and smoking (adjusted odds ratio=2.15; 95% confidence interval, 1.03-4.49).ConclusionNo baseline clinical factors predicted treatment success in women receiving medical management with misoprostol for early pregnancy loss. Adding mifepristone to the medical management regimen of early pregnancy loss improved treatment success; thus, mifepristone treatment should be considered for management of early pregnancy loss regardless of baseline clinical factors

Estimators for longitudinal latent exposure models: examining measurement model assumptions

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136711/1/sim7268_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136711/2/sim7268.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136711/3/sim7268-sup-0001-Supplementary.pd

Lasteaiaõpetajate ja lasteaiaõpetajaks õppivate üliõpilaste arusaam varajasest võõrkeeleõppest ning valmidus õpetada võõrkeeli lasteaias

https://www.ester.ee/record=b5248754*es

Sotsiaalpedagoogide tõlgendused kogukonna aspektist kooli ja kodu suhetes

http://tartu.ester.ee/record=b2656393~S6*es

Bayesian estimation of associations between identified longitudinal hormone subgroups and age at final menstrual period

Abstract Background Although follicle stimulating hormone (FSH) is known to be predictive of age at final menstrual period (FMP), previous methods use FSH levels measured at time points that are defined relative to the age at FMP, and hence are not useful for prospective prediction purposes in clinical settings where age at FMP is an unknown outcome. This study is aimed at assessing whether FSH trajectory feature subgroups identified relative to chronological age can be used to improve the prediction of age at FMP. Methods We develop a Bayesian model to identify latent subgroups in longitudinal FSH trajectories, and study the relationship between subgroup membership and age at FMP. Data for our study is taken from the Penn Ovarian Aging study, 1996–2010. The proposed model utilizes mixture modeling and nonparametric smoothing methods to capture hypothesized latent subgroup features of the FSH longitudinal trajectory; and simultaneously studies the prognostic value of these latent subgroup features to predict age at FMP. Results The analysis identified two FSH trajectory subgroups that were significantly associated with FMP age: 1) early FSH class (15 %), which displayed initial increases in FSH shortly after age 40; and 2) late FSH class (85 %), which did not have a rise in FSH until after age 45. The use of FSH subgroup memberships, along with class-specific characteristics, i.e., level and rate of FSH change at class-specific pre-specified ages, improved prediction of FMP age by 20–22 % in comparison to the prediction based on previously identified risk factors (BMI, smoking and pre-menopausal levels of anti-mullerian hormone (AMH)). Conclusions To the best of our knowledge, this work is the first in the area to demonstrate the existence of subgroups in FSH trajectory patterns relative to chronological age and the fact that such a subgroup membership possesses prediction power for age at FMP. Earlier ages at FMP were found in a subgroup of women with rise in FSH levels commencing shortly after age 40, in comparison to women who did not exhibit an increase in FSH until after 45 years of age. Periodic evaluations of FSH in these age ranges are potentially useful for predicting age at FMP.http://deepblue.lib.umich.edu/bitstream/2027.42/116209/1/12874_2015_Article_101.pd

A Latent Variable Transformation Model Approach for Exploring Dysphagia

Multiple outcomes are often collected in applications where the quantity of interest cannot be measured directly or is difficult or expensive to measure. In a head and neck cancer study conducted at Dana‐Farber Cancer Institute, the investigators wanted to determine the effect of clinical and treatment factors on unobservable dysphagia through collected multiple outcomes of mixed types. Latent variable models are commonly adopted in this setting. These models stipulate that multiple collected outcomes are conditionally independent given the latent factor. Mixed types of outcomes (e.g., continuous vs. ordinal) and censored outcomes present statistical challenges, however, as a natural analog of the multivariate normal distribution does not exist for mixed data. Recently, Lin et al . proposed a semiparametric latent variable transformation model for mixed outcome data; however, it may not readily accommodate event time outcomes where censoring is present. In this paper, we extend the work of Lin et al . by proposing both semiparametric and parametric latent variable models that allow for the estimation of the latent factor in the presence of measurable outcomes of mixed types, including censored outcomes. Both approaches allow for a direct estimate of the treatment (or other covariate) effect on the unobserved latent variable, greatly enhancing the interpretability of the models. The semiparametric approach has the added advantage of allowing the relationship between the measurable outcomes and latent variables to be unspecified, rendering more robust inference. The parametric and semiparametric models can also be used together, providing a comprehensive modeling strategy for complicated latent variable problems. Copyright © 2014 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108613/1/sim6239.pd

Wireless autonomous device data transmission

A method of communicating information from a wireless autonomous device (WAD) to a base station. The WAD has a data element having a predetermined profile having a total number of sequenced possible data element combinations. The method includes receiving at the WAD an RF profile transmitted by the base station that includes a triggering portion having a number of pulses, wherein the number is at least equal to the total number of possible data element combinations. The method further includes keeping a count of received pulses and wirelessly transmitting a piece of data, preferably one bit, to the base station when the count reaches a value equal to the stored data element's particular number in the sequence. Finally, the method includes receiving the piece of data at the base station and using the receipt thereof to determine which of the possible data element combinations the stored data element is

Usuvabaduse ja loomakaitse seosed Euroopa õiguskorras koduloomade rituaalse tapmise reguleerimisel

https://www.ester.ee/record=b5361778*es