Retaining principal components for discrete variables

The present study discusses retention criteria for principal components analysis (PCA) applied to Likert scale items typical in psychological questionnaires. The main aim is to recommend applied researchers to restrain from relying only on the eigenvalue-than-one criterion; alternative procedures are suggested for adjusting for sampling error. An additional objective is to add evidence on the consequences of applying this rule when PCA is used with discrete variables. The experimental conditions were studied by means of Monte Carlo sampling including several sample sizes, different number of variables and answer alternatives, and four non-normal distributions. The results suggest that even when all the items and thus the underlying dimensions are independent, eigenvalues greater than one are frequent and they can explain up to 80% of the variance in data, meeting the empirical criterion. The consequences of using Kaiser"s rule are illustrated with a clinical psychology example. The size of the eigenvalues resulted to be a function of the sample size and the number of variables, which is also the case for parallel analysis as previous research shows. To enhance the application of alternative criteria, an R package was developed for deciding the number of principal components to retain by means of confidence intervals constructed about the eigenvalues corresponding to lack of relationship between discrete variables.

Independent relations of left ventricular structure with the 24-h urinary excretion of sodium and aldosterone

Objective: Previous studies reported on the association of left ventricular mass index (LVMI) with urinary sodium or with circulating or urinary aldosterone.We investigated the independent associations of LVMI with the urinary excretion of both sodium and aldosterone. Design and method: We randomly recruited 317 untreated subjects from a White population (45.1%women; mean age 48.2 years).Measurements included echocardiographic left ventricular (LV) properties, the 24 h urinary excretion of sodium and aldosterone, plasma renin activity (PRA), and proximal (RNaprox) and distal (RNadist) renal sodium reabsorption, assessed fromthe endogenous lithium clearance. Inmultivariable-adjusted models,we expressed changes in LVMI per 1 SD increase in the explanatory variables, while accounting for sex, age, systolic blood pressure and the waist-to-hip ratio. Results: LVMI increased independentlywith the urinary excretion of both sodium (+2.48 g/m2; P=0.005) and aldosterone (+2.63 g/m2; P=0.004). Higher sodium excretion was associated with increased mean wall thickness (MWT: +0.126 mm, P=0.054), but with no change in LV end-diastolic diameter (LVID: +0.12mm, P=0.64). In contrast, higher aldosterone excretion was associated with higher LVID (+0.54 mm; P=0.017), but with no change in MWT (+0.070mm; P=0.28).Higher RNadistwas associatedwith lower relativewall thickness (−0.81×10−2, P=0.017), because of opposite trends in LVID(+0.33 mm; P=0.13) and MWT (−0.130mm; P=0.040). LVMI was not associated with PRA or RNaprox. Conclusions: LVMI independently increased with both urinary sodium and aldosterone excretion. IncreasedMWT explained the association of LVMI with urinary sodium and increased LVID the association of LVMI with urinary aldosterone.

Dry matter production of Tanzania grass as a function of agrometeorological variables

The objective of this work was to develop and validate linear regression models to estimate the production of dry matter by Tanzania grass (Megathyrsus maximus, cultivar Tanzania) as a function of agrometeorological variables. For this purpose, data on the growth of this forage grass from 2000 to 2005, under dry‑field conditions in São Carlos, SP, Brazil, were correlated to the following climatic parameters: minimum and mean temperatures, degree‑days, and potential and actual evapotranspiration. Simple linear regressions were performed between agrometeorological variables (independent) and the dry matter accumulation rate (dependent). The estimates were validated with independent data obtained in São Carlos and Piracicaba, SP, Brazil. The best statistical results in the development and validation of the models were obtained with the agrometeorological parameters that consider thermal and water availability effects together, such as actual evapotranspiration, accumulation of degree‑days corrected by water availability, and the climatic growth index, based on average temperature, solar radiation, and water availability. These variables can be used in simulations and models to predict the production of Tanzania grass.

Method of numerical correction of errors occasioned by delay of records during the monitoring of environmental variables of interest for animal production

Thermal and air conditions inside animal facilities change during the day due to the influence of the external environment. For statistical and geostatistical analyses to be representative, a large number of points spatially distributed in the facility area must be monitored. This work suggests that the time variation of environmental variables of interest for animal production, monitored within animal facility, can be modeled accurately from discrete-time records. The aim of this study was to develop a numerical method to correct the temporal variations of these environmental variables, transforming the data so that such observations are independent of the time spent during the measurement. The proposed method approached values recorded with time delays to those expected at the exact moment of interest, if the data were measured simultaneously at the moment at all points distributed spatially. The correction model for numerical environmental variables was validated for environmental air temperature parameter, and the values corrected by the method did not differ by Tukey's test at 5% significance of real values recorded by data loggers.

Night admission is an independent risk factor for mortality in trauma patients - a systemic error approach

ABSTRACTObjective:to assess the impact of the shift inlet trauma patients, who underwent surgery, in-hospital mortality.Methods:a retrospective observational cohort study from November 2011 to March 2012, with data collected through electronic medical records. The following variables were statistically analyzed: age, gender, city of origin, marital status, admission to the risk classification (based on the Manchester Protocol), degree of contamination, time / admission round, admission day and hospital outcome.Results:during the study period, 563 patients injured victims underwent surgery, with a mean age of 35.5 years (± 20.7), 422 (75%) were male, with 276 (49.9%) received in the night shift and 205 (36.4%) on weekends. Patients admitted at night and on weekends had higher mortality [19 (6.9%) vs. 6 (2.2%), p=0.014, and 11 (5.4%) vs. 14 (3.9%), p=0.014, respectively]. In the multivariate analysis, independent predictors of mortality were the night admission (OR 3.15), the red risk classification (OR 4.87), and age (OR 1.17).Conclusion:the admission of night shift and weekend patients was associated with more severe and presented higher mortality rate. Admission to the night shift was an independent factor of surgical mortality in trauma patients, along with the red risk classification and age.

Correlation of serum leptin and insulin levels of pregnant protein-restricted rats with predictive obesity variables

During pregnancy and protein restriction, changes in serum insulin and leptin levels, food intake and several metabolic parameters normally result in enhanced adiposity. We evaluated serum leptin and insulin levels and their correlations with some predictive obesity variables in Wistar rats (90 days), up to the 14th day of pregnancy: control non-pregnant (N = 5) and pregnant (N = 7) groups (control diet: 17% protein), and low-protein non-pregnant (N = 5) and pregnant (N = 6) groups (low-protein diet: 6%). Independent of the protein content of the diet, pregnancy increased total (F1,19 = 22.28, P < 0.001) and relative (F1,19 = 5.57, P < 0.03) food intake, the variation of weight (F1,19 = 49.79, P < 0.000) and final body weight (F1,19 = 19.52, P < 0.001), but glycemia (F1,19 = 9.02, P = 0.01) and the relative weight of gonadal adipose tissue (F1,19 = 17.11, P < 0.001) were decreased. Pregnancy (F1,19 = 18.13, P < 0.001) and low-protein diet (F1,19 = 20.35, P < 0.001) increased the absolute weight of brown adipose tissue. However, the relative weight of this tissue was increased only by protein restriction (F1,19 = 15.20, P < 0.001) and the relative lipid in carcass was decreased in low-protein groups (F1,19 = 4.34, P = 0.05). Serum insulin and leptin levels were similar among groups and did not correlate with food intake. However, there was a positive relationship between serum insulin levels and carcass fat depots in low-protein groups (r = 0.37, P < 0.05), while in pregnancy serum leptin correlated with weight of gonadal (r = 0.39, P < 0.02) and retroperitoneal (r = 0.41, P < 0.01) adipose tissues. Unexpectedly, protein restriction during 14 days of pregnancy did not alter the serum profile of adiposity signals and their effects on food intake and adiposity, probably due to the short term of exposure to low-protein diet.

Modélisation des bi-grappes et sélection des variables pour des données de grande dimension : application aux données d’expression génétique

Les simulations ont été implémentées avec le programme Java.

Interpretation of wind components as compositional variables

The classical statistical study of the wind speed in the atmospheric surface layer is made generally from the analysis of the three habitual components that perform the wind data, that is, the component W-E, the component S-N and the vertical component, considering these components independent. When the goal of the study of these data is the Aeolian energy, so is when wind is studied from an energetic point of view and the squares of wind components can be considered as compositional variables. To do so, each component has to be divided by the module of the corresponding vector. In this work the theoretical analysis of the components of the wind as compositional data is presented and also the conclusions that can be obtained from the point of view of the practical applications as well as those that can be derived from the application of this technique in different conditions of weather

Complicaciones de la preeclampsia severa y su relación con variables demográficas y obstétricas

Introducción: La preeclampsia severa es una de las principales patologías que afectan a las mujeres embarazadas, sus complicaciones tienen un alto impacto en la salud del binomio madre-hijo. Materiales y métodos: Se realizo una serie de casos, durante un periodo de 1 año se revisaron las historias clínicas de las pacientes que ingresaron a la unidad de cuidado intensivo obstétrico de la Clínica Orquídeas, con diagnóstico de preeclampsia severa. Se describieron los datos demográficos y las complicaciones. Se realizó análisis univariado con las variables de interés y se calcularon diferencias significativas por medio del test exacto de Fisher. Resultados: Se registraron 196 pacientes con preeclampsia severa en el periodo de estudio. Las complicaciones mas frecuentes fueron síndrome HELLP (30,6%), insuficiencia renal aguda (16,3%) y edema pulmonar (10,2%); el ingreso de las pacientes con preeclampsia severa a la UCIO en embarazo aumenta el riesgo de sufrir complicaciones. El síndrome de HELLP se presento con mayor frecuencia en pacientes que realizaron 6 o mas controles prenatales (p=0.066). Discusión: Los resultados evidencian una prevalencia de preeclampsia severa mayor que la observada por otros autores, probablemente por ser una UCI exclusivamente obstétrica. Las complicaciones mas frecuentes son concordantes con otros estudios publicados. El mayor riesgo de complicaciones asociadas en pacientes que ingresan embarazadas a la UCIO podría estar en relación a la severidad de la patología. Se requieren estudios analíticos para establecer asociaciones entre cada una de las complicaciones y sus factores condicionantes.

Caracterización de las variables nutricionales en pacientes incidentes de diálisis peritoneal rts 2011-2012

Los pacientes con enfermedad renal crónica (ERC) terminal se caracterizan por presentar alteraciones nutricionales que se perpetúan independiente de la modalidad de la Terapia de Reemplazo Renal (TRR). En la diálisis peritoneal, tanto APD (automated peritoneal dialysis) como la CAPD (continuous ambulatory peritoneal dialysis) existe un alto riesgo de pérdida de albúmina por el filtrado peritoneal, sin diferencias claras en el estatus nutricional. El presente estudio caracteriza el estado nutricional de los pacientes incidentes en diálisis peritoneal de RTS Bogotá Regional 1, con un seguimiento de un año, para conocer los cambios en las variables nutricionales. Se realizó un estudio de cohortes retrospectivo, analizando 2 grupos según el tipo de diálisis peritoneal escogida (APD o CAPD), con un análisis análisis descriptivo trimestral de las características nutricionales y posteriormente una comparación entre las 2 modalidades de TRR. Encontrando un promedio de edad de 60,8 años, la mayoría hombres y etiología principal nefropatía diabética. La mayoría de las variables nutricionales permanecieron sin cambios durante seguimiento. El Test de equilibrio peritoneal para glucosa y creatinina mostró valores promedio bajo y promedio alto y la mayoría de pacientes un rango nutricional normal. Al comparar APD y CAPD, solo se encontraron de forma aislada, diferencias significativas en algunas variables aisladas. Este es el primer estudio en Colombia que evalúa diferentes aspectos nutricionales en diálisis peritoneal. Aunque con limitaciones metodológicas, es un punto de partida para la realización de estudios más robustos que del estado nutricional de los pacientes en diálisis peritoneal

A study of variables that may influence continued placement in schools for the deaf

This paper reviews variables that influence placement of a hearing impaired child into a special education program instead of being mainstreamed into a public school.

A study of variables influencing placement in schools for hearing

This paper reviews mainstreaming of former students of CID, 1965-1975.

Variables that influence the real-ear response of the TDH-49 earphone

This paper discusses a study performed to determine whether anatomical features of the outer ear affect the sound stimulus delivered by earphone to the tympanic membrane.

Operations on Risk Variables

In the article the author considers and analyzes operations and functions on risk variables. She takes into account the following variables: the sum of risk variables, its product, multiplication by a constant, division, maximum, minimum and median of a sum of random variables. She receives the formulas for probability distribution and basic distribution parameters. She conducts the analysis for dependent and independent random variables. She propose the examples of the situations in the economy and production management of risk modelled by this operations. The analysis is conducted with the way of mathematical proving. Some of the formulas presented are taken from the literature but others are the permanent results of the author.

The underlying return generating factors for REIT returns: an application of independent component analysis

Multi-factor approaches to analysis of real estate returns have, since the pioneering work of Chan, Hendershott and Sanders (1990), emphasised a macro-variables approach in preference to the latent factor approach that formed the original basis of the arbitrage pricing theory. With increasing use of high frequency data and trading strategies and with a growing emphasis on the risks of extreme events, the macro-variable procedure has some deficiencies. This paper explores a third way, with the use of an alternative to the standard principal components approach – independent components analysis (ICA). ICA seeks higher moment independence and maximises in relation to a chosen risk parameter. We apply an ICA based on kurtosis maximisation to weekly US REIT data using a kurtosis maximising algorithm. The results show that ICA is successful in capturing the kurtosis characteristics of REIT returns, offering possibilities for the development of risk management strategies that are sensitive to extreme events and tail distributions.