9 resultados para Logit fixed effect model
em Dalarna University College Electronic Archive
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This paper investigates what factors affect the destination choice for Jordanian to 8 countries (Oman, Saudi Arabia, Syria, Tunisia, Yemen, Egypt, Lebanon and Bahrain) using panel data analysis. Number of outbound tourists is represented as dependent variable, which is regressed over five explanatory variables using fixed effect model. The finding of this paper is that tourists from Jordan have weak demand for outbound tourism; Jordanian decision of traveling abroad is determined by the cost of traveling to different places and choosing the cheapest alternative.
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Objective Levodopa in presence of decarboxylase inhibitors is following two-compartment kinetics and its effect is typically modelled using sigmoid Emax models. Pharmacokinetic modelling of the absorption phase of oral distributions is problematic because of irregular gastric emptying. The purpose of this work was to identify and estimate a population pharmacokinetic- pharmacodynamic model for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Methods The modelling involved pooling data from two studies and fixing some parameters to values found in literature (Chan et al. J Pharmacokinet Pharmacodyn. 2005 Aug;32(3-4):307-31). The first study involved 12 patients on 3 occasions and is described in Nyholm et al. Clinical Neuropharmacology 2003:26:156-63. The second study, PEDAL, involved 3 patients on 2 occasions. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Plasma samples and motor ratings (clinical assessment of motor function from video recordings on a treatment response scale between -3 and 3, where -3 represents severe parkinsonism and 3 represents severe dyskinesia.) were repeatedly collected until the clinical effect was back at baseline. At this point, the usual infusion rate was started and sampling continued for another two hours. Different structural absorption models and effect models were evaluated using the value of the objective function in the NONMEM package. Population mean parameter values, standard error of estimates (SE) and if possible, interindividual/interoccasion variability (IIV/IOV) were estimated. Results Our results indicate that Duodopa absorption can be modelled with an absorption compartment with an added bioavailability fraction and a lag time. The most successful effect model was of sigmoid Emax type with a steep Hill coefficient and an effect compartment delay. Estimated parameter values are presented in the table. Conclusions The absorption and effect models were reasonably successful in fitting observed data and can be used in simulation experiments.
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Backgound and aims: The main purpose of the PEDAL study is to identify and estimate sample individual pharmacokinetic- pharmacodynamic (PK/PD) models for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Other objectives are to study the absorption of Duodopa® and to form a basis for power calculation for a future larger study. PK/PD based on oral levodopa is problematic because of irregular gastric emptying. Preliminary work with data from [Gundert-Remy U et al. Eur J Clin Pharmacol 1983;25:69-72] suggested that levodopa infusion pharmacokinetics can be described by a two-compartment model. Background research led to a hypothesis for an effect model incorporating concentration-unrelated fluctuations, more complex than standard E-max models. Methods: PEDAL involved a few patients already on Duodopa®. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Data collection continued until the clinical effect was back at baseline. The procedure was repeated on two non-consecutive days per patient. The following data were collected in 5 to 15 minutes intervals: i) Accelerometer data. ii) Three e-diary questions about ability to walk, feelings of “off” and “dyskinesia”. iii) Clinical assessment of motor function by a physician. iv) Plasma concentrations of levodopa, carbidopa and the metabolite 3-O-methyldopa. The main effect variable will be the clinical assessment. Results: At date of abstract submission, lab analyses were currently being performed. Modelling results, simulation experiments and conclusions will be presented in our poster.
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Objective To investigate if a home environment test battery can be used to measure effects of Parkinson’s disease (PD) treatment intervention and disease progression. Background Seventy-seven patients diagnosed with advanced PD were recruited in an open longitudinal 36-month study at 10 clinics in Sweden and Norway; 40 of them were treated with levodopa-carbidopa intestinal gel (LCIG) and 37 patients were candidates for switching from oral PD treatment to LCIG. They utilized a mobile device test battery, consisting of self-assessments of symptoms and objective measures of motor function through a set of fine motor tests (tapping and spiral drawings), in their homes. Both the LCIG-naïve and LCIG-non-naïve patients used the test battery four times per day during week-long test periods. Methods Assessments The LCIG-naïve patients used the test battery at baseline (before LCIG), month 0 (first visit; at least 3 months after intraduodenal LCIG), and thereafter quarterly for the first year and biannually for the second and third years. The LCIG-non-naïve patients used the test battery from the first visit, i.e. month 0. Out of the 77 patients, only 65 utilized the test battery; 35 were LCIG-non-naïve and 30 LCIG-naïve. In 20 of the LCIG-naïve patients, assessments with the test battery were available during oral treatment and at least one test period after having started infusion treatment. Three LCIG-naïve patients did not use the test battery at baseline but had at least one test period of assessments thereafter. Hence, n=23 in the LCIG-naïve group. In total, symptom assessments in the full sample (including both patient groups) were collected during 379 test periods and 10079 test occasions. For 369 of these test periods, clinical assessments including UPDRS and PDQ-39 were performed in afternoons at the start of the test periods. The repeated measurements of the test battery were processed and summarized into scores representing patients’ symptom severities over a test period, using statistical methods. Six conceptual dimensions were defined; four subjectively-reported: ‘walking’, ‘satisfied’, ‘dyskinesia’, and ‘off’ and two objectively-measured: ‘tapping’ and ‘spiral’. In addition, an ‘overall test score’ (OTS) was defined to represent the global health condition of the patient during a test period. Statistical methods Change in the test battery scores over time, that is at baseline and follow-up test periods, was assessed with linear mixed-effects models with patient ID as a random effect and test period as a fixed effect of interest. The within-patient variability of OTS was assessed using intra-class correlation coefficient (ICC), for the two patient groups. Correlations between clinical rating scores and test battery scores were assessed using Spearman’s rank correlations (rho). Results In LCIG-naïve patients, mean OTS compared to baseline was significantly improved from the first test period on LCIG treatment until month 24. However, there were no significant changes in mean OTS scores of LCIG-non-naïve patients, except for worse mean OTS at month 36 (p<0.01, n=16). The mean scores of all subjectively-reported dimensions improved significantly throughout the course of the study, except ‘walking’ at month 36 (p=0.41, n=4). However, there were no significant differences in mean scores of objectively-measured dimensions between baseline and other test periods, except improved ‘tapping’ at month 6 and month 36, and ‘spiral’ at month 3 (p<0.05). The LCIG-naïve patients had a higher within-subject variability in their OTS scores (ICC=0.67) compared to LCIG-non-naïve patients (ICC=0.71). The OTS correlated adequately with total UPDRS (rho=0.59) and total PDQ-39 (rho=0.59). Conclusions In this 3-year follow-up study of advanced PD patients treated with LCIG we found that it is possible to monitor PD progression over time using a home environment test battery. The significant improvements in the mean OTS scores indicate that the test battery is able to measure functional improvement with LCIG sustained over at least 24 months.
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We consider methods for estimating causal effects of treatment in the situation where the individuals in the treatment and the control group are self selected, i.e., the selection mechanism is not randomized. In this case, simple comparison of treated and control outcomes will not generally yield valid estimates of casual effects. The propensity score method is frequently used for the evaluation of treatment effect. However, this method is based onsome strong assumptions, which are not directly testable. In this paper, we present an alternative modeling approachto draw causal inference by using share random-effect model and the computational algorithm to draw likelihood based inference with such a model. With small numerical studies and a real data analysis, we show that our approach gives not only more efficient estimates but it is also less sensitive to model misspecifications, which we consider, than the existing methods.
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Setup time reduction facilitate the flexibility needed for just-in-time production. An integrated steel mill with meltshop, continuous caster and hot rolling mill is often operated as decoupled processes. Setup time reduction provides the flexibility needed to reduce buffering, shorten lead times and create an integrated process flow. The interdependency of setup times, process flexibility and integration were analysed through system dynamics simulation. The results showed significant reductions of energy consumption and tied capital. It was concluded that setup time reduction in the hot strip mill can aid process integration and hence improve production economy while reducing environmental impact.
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This paper examines whether European Monetary Union (EMU) countries share fairly the effect of their membership in Eurozone (EZ) or whether are winners and losers in this ''Euro-game''. By using panel data of 27 European Union (EU) Member States for the period 2001-2012 in the context of a gravity model, we focus on estimating the Euro’s effect on bilateral trade and we detect whether this effect differs across the Member States of EZ. Two estimation methods are applied: Pooled OLS estimator and Fixed Effects estimator. The empirical results come to the conclusion that the individual country effects differ and are statistically significant, indicating that EMU’s effect on trade differs across the Member States of EZ. The overall effect of the Euro is statistically insignificant, regardless the estimation method, demonstrating that the common European currency may have no effect on bilateral trade.