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Intermediate Variables (intermediate + variable)
Selected AbstractsA two-step predictive control design for input saturated Hammerstein systemsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 7 2006Baocang Ding Abstract The two-step model predictive control is designed for input saturated Hammerstein systems. It first applies the unconstrained linear dynamic subsystem to get the desired intermediate variable, and then obtains the actual control action by solving nonlinear algebraic equation group and desaturation. The stability of the closed-loop system is analysed and its domain of attraction is designed applying semi-global stabilization techniques. The stability conclusions are illustrated with an example. Copyright © 2006 John Wiley & Sons, Ltd. [source] Sensitivity Analysis for Principal Stratum Direct Effects, with an Application to a Study of Physical Activity and Coronary Heart DiseaseBIOMETRICS, Issue 2 2009Arvid Sjölander Summary In many studies, the aim is to learn about the direct exposure effect, that is, the effect not mediated through an intermediate variable. For example, in circulation disease studies it may be of interest to assess whether a suitable level of physical activity can prevent disease, even if it fails to prevent obesity. It is well known that stratification on the intermediate may introduce a so-called posttreatment selection bias. To handle this problem, we use the framework of principal stratification (Frangakis and Rubin, 2002, Biometrics58, 21,29) to define a causally relevant estimand,the principal stratum direct effect (PSDE). The PSDE is not identified in our setting. We propose a method of sensitivity analysis that yields a range of plausible values for the causal estimand. We compare our work to similar methods proposed in the literature for handling the related problem of "truncation by death." [source] Stimulation day-six serum estradiol: A predictive indicator for the probability of embryo cryopreservation in IVF/ICSI cyclesJOURNAL OF OBSTETRICS AND GYNAECOLOGY RESEARCH (ELECTRONIC), Issue 2 2009Hassan A. El Maghraby Abstract Objective:, To evaluate the predictive value of stimulation day six serum estradiol (E2) for the probability of embryo cryopreservation after fresh embryo transfer in intracytoplasmic sperm injection (ICSI) cycles. Subjects and Methods:, The study included 282 ICSI cycles for different causes of infertility, provided that the age of the female partner was <40 years and her basal follicle stimulating hormone <10 IU/L. Setting:, Alexandria IVF/ICSI center. Main Outcome Measures:, Primary outcome measures are stimulation day-six serum E2, and rate of embryo cryopreservation, after transfer of three good-quality embryos. Secondary outcome measures are pregnancy rate per fresh embryo transfer, and other intermediate variables of the ICSI cycle. Results:, Patients were stratified into three groups according to day-six serum E2 levels: Group I with values <400 pg/mL; Group II, between 400 and 900; and Group III with values >900. The mean number of oocytes retrieved was 6.3, 8.9, and 12.4; the mean number of obtained embryos was 3.3, 4.8, and 6.7; and pregnancy rates were 18.1, 36.2, and 44.7% in the three groups, respectively. Rate of embryo cryopreservation, after transfer of three good-quality embryos was 70.7% in Group III, and 26.5% in Group I. (P = 0.01). The negative predictive value of day-six E2 < 400 pg/mL for freezing was 83% while day-six serum E2 > 900 pg/mL has a sensitivity of 55%, specificity of 72% and positive predictive value of 50% for embryo freezing. Conclusion:, Higher stimulation day-six estradiol was associated with a higher probability of cryopreservation, and a higher pregnancy rate. [source] School-Based Health Centers and Academic Performance: Research, Challenges, and RecommendationsJOURNAL OF SCHOOL HEALTH, Issue 9 2004Sara Peterson Geierstanger ABSTRACT: School-based health centers (SBHCs) provide physical and mental health services on school campuses to improve student health status, and thereby potentially facilitate student academic success. With a growing emphasis on school accountability and the simultaneous dwindling of resources at the federal, state, and local levels, SBHCs face increasing pressures from school administrators and funders to document their impact on student academic achievement. This article reviews the methods, findings, and limitations of studies that have examined the relationship between SBHCs and academic performance. It also describes methodological challenges of conducting and interpreting such research, and discusses factors and intermediate variables that influence student academic performance. Recommendations are offered for SBHC researchers, evaluators, and service providers in response to the pressure they are facing to document the effect of SBHC services on academic outcomes. (J Sch Health. 2004;74(9):347,352) [source] Risk Factor Adjustment in Marginal Structural Model Estimation of Optimal Treatment RegimesBIOMETRICAL JOURNAL, Issue 5 2009Erica E. M. Moodie Abstract Marginal structural models (MSMs) are an increasingly popular tool, particularly in epidemiological applications, to handle the problem of time-varying confounding by intermediate variables when studying the effect of sequences of exposures. Considerable attention has been devoted to the optimal choice of treatment model for propensity score-based methods and, more recently, to variable selection in the treatment model for inverse weighting in MSMs. However, little attention has been paid to the modeling of the outcome of interest, particularly with respect to the best use of purely predictive, non-confounding variables in MSMs. Four modeling approaches are investigated in the context of both static treatment sequences and optimal dynamic treatment rules with the goal of estimating a marginal effect with the least error, both in terms of bias and variability. [source] | |||||||||||||