Longitudinal Spline Research Articles

PEMODELAN HARGA SAHAM PERUSAHAAN PROPERTI DAN REAL ESTATE MENGGUNAKAN REGRESI LONGITUDINAL SPLINE TRUNCATED DILENGKAPI GUI R

Stocks are one of the most popular financial instruments traded in the capital market. One of stock prices fluctuate up and down due to the influence of several factors, one of which is inflation. Stocks in the property and real estate sectors are important indicators to determine the level of a country economy. Data on several stock prices is one case of longitudinal data in economic field. The data is divided into 2 parts, namely in sample data from January 2016 to October 2020 and out sample data from November 2020 to December 2021. In this study, longitudinal stock price data is modeling using nonparametric spline truncated. The best spline truncated model is determined by the order and the optimal number of knot points based on the minimum Generalized Cross Validation value. Spline truncated nonparametric regression modeling for longitudinal data in this study is equipped with Graphical User Interface (GUI) that can facilitate the data processing. The results of the analysis show that the best longitudinal spline truncated regression model obtained on 2nd order with 5 knot points. 95.04% value of indicates the model is a strong model. In the evaluation of the best model, the MAPE data out sample value is 16.45%. It indicates the model has good forecasting ability.

Weight loss interventions on health-related quality of life in those with moderate to severe obesity: Findings from an individual patient data meta-analysis of randomized trials.

The relationship between BMI and health-related quality of life (HRQoL) critically affects regulatory approval of interventions for weight loss, but evidence of the association is inconsistent. A higher standard of evidence than that available was sought with an IPD meta-analysis of 10,884 people enrolled in five randomized controlled trials of intentional weight loss interventions. Cross-sectional and longitudinal associations of BMI and HRQoL were estimated in mixed effects models specifying a latent variable for HRQoL. Spline regressions captured nonlinear associations across the range of BMI. In cross-sectional spline regressions, BMI was not associated with HRQoL for people with a BMI < 30 kg/m2 but was for those with a higher BMI. In longitudinal spline regressions, decreases in BMI were positively associated with HRQoL for people with a BMI ≥ 25 kg/m2 . The impact of change in BMI was larger for people with higher BMIs than for those with BMIs under 30 kg/m2 . Lower BMI and decreases in BMI were related to higher HRQoL for people living with obesity but not in the population without excess weight. HRQoL gains from weight loss are greater for more severe obesity. Commissioners should use these estimates for future decision making.

Postbuckling analysis of orthogonally-stiffened plates by a simplified spline finite strip method

Postbuckling behavior of stiffened laminated composite plates is investigated using a simplified spline finite strip method. The base plate and stiffeners are formulated by the first-order shear deformation plate theory and the Timoshenko beam theory, respectively. According to the compatibility condition between the base plate and stiffener, the beam displacements are expressed by the fundamental middle surface displacement component functions of the base plate. The beam-plate assembly is then discretized exclusively by the base plate strips. The longitudinal spline interpolation coefficients of the strip are transformed into actual freedoms of each nodal line, so that the stiffness contribution of transverse stiffeners can be easily incorporated into the strips. The nonlinear governing equation is solved using the Newton–Raphson method. The present beam-plate model is applicable to both global and local plate postbuckling analyses of stiffened plates, and the modification of the spline interpolation makes the spline finite strip method (SFSM) versatile for both the transversely- and orthogonally-stiffened plates. The effectiveness and capability of developed postbuckling analysis are verified by comparisons with numerical finite element results. Parametric studies are conducted to investigate postbuckling behavior of stiffened laminated composite plates. The present simplified SFSM is capable of performing both the critical buckling load prediction and postbuckling analysis of either transversely-stiffened or orthogonally-stiffened laminated composite plates.

Early Elective Delivery Disparities between Non-Hispanic Black and White Women after Statewide Policy Implementation

BackgroundIn 2011, Oregon implemented a policy that reduced the state's rate of early (before 39 weeks' gestation) elective (without medical need) births. ObjectiveThis analysis measured differential policy effects by race, examining whether Oregon's policy was associated with changes in non-Hispanic Black–White disparities in early elective cesarean and labor induction. MethodsWe used Oregon birth certificate data, defining prepolicy (2008–2010) and postpolicy (2012–2014) periods, including non-Hispanic Black and White women who gave birth during these periods (n = 121,272). We used longitudinal spline models to assess policy impacts by race and probability models to measure policy-associated changes in Black–White disparities. ResultsWe found that the prepolicy Black–White differences in early elective cesarean (6.1% vs. 4.3%) were eliminated after policy implementation (2.8% vs. 2.5%); adjusted models show decreases in the odds of elective early cesarean among Black women after the policy change (adjusted odds ratio, 0.47; 95% confidence interval, 0.22–1.00; p = .050) and among White women (adjusted odds ratio, 0.79; 95% confidence interval, 0.67–0.93; p = .006). Adjusted probability models indicated that policy implementation resulted in a 1.75-percentage point narrowing (p = .011) in the Black–White disparity in early elective cesarean. Early elective induction also decreased, from 4.9% and 4.7% for non-Hispanic Black and non-Hispanic White women to 3.8% and 2.5%, respectively; the policy was not associated with a statistically significant change in disparities. ConclusionsA statewide policy reduced racial disparities in early elective cesarean, but not early elective induction. Attention to differential policy effects by race may reveal changes in disparities, even when that is not the intended focus of the policy.

Predictive performance of a semiparametric method to estimate population pharmacokinetic parameters using NONMEM.

Routine clinical pharmacokinetic (PK) data collected from patients receiving inulin were analyzed to estimate population PK parameters; 560 plasma concentration determinations for inulin were obtained from 90 patients. The data were analyzed using NONMEM. The population PK parameters were estimated using a Constrained Longitudinal Splines (CLS) semiparametric approach and a first-order conditional method (FOCE). The mean posterior individual clearance values were 7.73 L/hr using both parametric and semiparametric methods. This estimation was compared with clearances estimated using standard nonlinear weighted least squares approach (reference value, 7.64 L/hr). The bias was not statistically different from zero and the precision of the estimates was 0.415 L/hr using parametric method and 0.984 L/hr using semiparametric method. To evaluate the predictive performances of the population parameters, 17 new subjects were used. First, the individual inulin clearance values were estimated from drug concentration-time curve using a nonlinear weighted least-squares method then they were estimated using the NONMEM POSTHOC method obtained using parametric and CLS methods as well as an alternative method based on a Monte Carlo simulation approach. The population parameters combined with two individual inulin plasma concentrations (0.25 and 2 hr) led to an estimation of individual clearances without bias and with a good precision. This paper not only evaluates the relative performance of the parametric and the CLS methods for sparse data but also introduces a new method for individual estimation.

A semiparametric method for describing noisy population pharmacokinetic data.

We propose a semiparametric method to estimate model-independent pharmacokinetic (PK) measures such as area under concentration-time, peak concentration and time to peak concentration (Tpeak), for noisy population PK data from a sparsely sampled prospectively designed trial. The method is developed within the mixed-effect model framework, for the single-dose and steady-state case. We describe individual concentration vs. time using a longitudinal spline, consisting of a template spline, common to all individuals, and an individual-specific distortion spline accounting for individual differences. We impose a number of constraints on the longitudinal spline, including (i) it has a decreasing tail, (ii) its typical Tpeak is near the modal Tpeak observed in the population data, and (iii) its value is zero at time zero (single dose), or the same nonzero value at the beginning and end of a dosing interval (steady state). We test our method using simulated data and compare its performance to that of a parametric and a nonparametric method. An actual data example is also shown. The performance of the method is as good or better than that of a standard nonparametric method, and when the analysis model is misspecified, the method is superior to a standard parametric one. Since it is often not apparent that an analysis model is correct, we propose this approach as a general method for analysis.

A nonparametric subject-specific population method for deconvolution: I. Description, internal validation, and real data examples.

In a pharmacokinetics context deconvolution facilitates the following: (i) Given data obtained after intravascular (generally intravenous) input one may estimate the disposition function; (ii) given the disposition function and data obtained after extravascular administration one may estimate the extravascular to vascular input rate function. In general if the data can be represented by the convolution of two functions, of which one is unknown, deconvolution allows the estimation of the unknown one. Attention has been given in the past to deconvolution and in particular to its nonparametric variants. However, in a population context (multiple observations collected in each of a group of subjects) the use of nonparametric deconvolution is limited to either analyzing each subject separately or to analyzing the aggregate response from the population without specifying subject-specific characteristics. To our knowledge a fully nonparametric deconvolution method in which subject specificity is explicitly taken into account has not been reported. To do so we use so-called "longitudinal splines." A longitudinal spline is a nonparametric function composed of a template spline, in common to all subjects, and of a distortion spline representing the difference of the subject's function from the template. Using longitudinal splines for input rate or disposition function one obtains a solution to the problem of taking subject specificity into account in a nonparametric deconvolution context. To obtain estimates of longitudinal splines we consider three different methods: (1) parametric nonlinear mixed effect, (2) least squares, and (3) two-stage. Results obtained in one simulated and two real data analyses are shown.

A nonparametric subject-specific population method for deconvolution: II. External validation.

A lot of attention has been given in the past to deconvolution and in particular to its nonparametric variants. In a companion paper (1), we present a fully nonparametric deconvolution method in which subject specificity is explicitly taken into account. To do so we use so-called "longitudinal splines." A longitudinal spline is a nonparametric function composed of a template spline, in common to all subjects, and of a distortion spline representing the difference of the subject's function from the template. In this paper we concentrate on testing and documenting the performance of this nonparametric methodology in terms of the approximation of unknown functions. We simulate population data using parametric functions, and use longitudinal splines to recover the unknown functions. We consider different estimation methods including (1) parametric nonlinear mixed effect, (2) least squares, and (3) two-stage. Methods 2-3 are more robust than Method 1, and obtain reliable estimates of the unknown functions. The lack of robustness of Method 1 appears to be due to the misspecifications of the distribution of the subjects' parameters. Results also suggest that in a data-rich situation nonparametric nonlinear mixed-effect models should be preferred.

STATIC ANALYSIS OF RIGHT BOX GIRDER BRIDGES BY SPLINE FINITE STRIP MET -HOD.

Keywords HONG KONG UNIVERSITY, HALCROW ASIA STATIC, ANALYSIS, BOX, GIRDERS, BRIDGES, SPLINE, FINITE STRIP, METHODS, DISPLACEMENT, STRIP, FUNCTIONS, LONGITUDINAL, CONVENTIONAL, TRANSVERSE, SHAPE, ENDS, INTERIOR, SUPPORTS, PROBLEMS, MATRIX, MATRICES, STRUCTURAL, THEORY, COMPUTERS, PROGRAMS, SYSTEMS, SOLUTIONS, ANALYTICAL, LOADS, NUMERICAL, FORMULATION... Show All