952 resultados para Least Square Method
Resumo:
The factor structure of a back translated Spanish version (Lega, Caballo and Ellis, 2002) of the Attitudes and Beliefs Inventory (ABI) (Burgess, 1990) is analyzed in a sample of 250 university students.The Spanish version of the ABI is a 48-items self-report inventory using a 5-point Likert scale that assesses rational and irrational attitudes and beliefs. 24-items cover two dimensions of irrationality: a) areas of content (3 subscales), and b) styles of thinking (4 subscales).An Exploratory Factor Analysis (Parallel Analysis with Unweighted Least Squares method and Promin rotation) was performed with the FACTOR 9.20 software (Lorenzo-Seva and Ferrando, 2013).The results reproduced the main four styles of irrational thinking in relation with the three specific contents of irrational beliefs. However, two factors showed a complex configuration with important cross-loadings of different items in content and style. More analyses are needed to review the specific content and style of such items.
Resumo:
The factor structure of a back translated Spanish version (Lega, Caballo and Ellis, 2002) of the Attitudes and Beliefs Inventory (ABI) (Burgess, 1990) is analyzed in a sample of 250 university students.The Spanish version of the ABI is a 48-items self-report inventory using a 5-point Likert scale that assesses rational and irrational attitudes and beliefs. 24-items cover two dimensions of irrationality: a) areas of content (3 subscales), and b) styles of thinking (4 subscales).An Exploratory Factor Analysis (Parallel Analysis with Unweighted Least Squares method and Promin rotation) was performed with the FACTOR 9.20 software (Lorenzo-Seva and Ferrando, 2013).The results reproduced the main four styles of irrational thinking in relation with the three specific contents of irrational beliefs. However, two factors showed a complex configuration with important cross-loadings of different items in content and style. More analyses are needed to review the specific content and style of such items.
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BACKGROUND: Health professionals and policymakers aspire to make healthcare decisions based on the entire relevant research evidence. This, however, can rarely be achieved because a considerable amount of research findings are not published, especially in case of 'negative' results - a phenomenon widely recognized as publication bias. Different methods of detecting, quantifying and adjusting for publication bias in meta-analyses have been described in the literature, such as graphical approaches and formal statistical tests to detect publication bias, and statistical approaches to modify effect sizes to adjust a pooled estimate when the presence of publication bias is suspected. An up-to-date systematic review of the existing methods is lacking. METHODS/DESIGN: The objectives of this systematic review are as follows:âeuro¢ To systematically review methodological articles which focus on non-publication of studies and to describe methods of detecting and/or quantifying and/or adjusting for publication bias in meta-analyses.âeuro¢ To appraise strengths and weaknesses of methods, the resources they require, and the conditions under which the method could be used, based on findings of included studies.We will systematically search Web of Science, Medline, and the Cochrane Library for methodological articles that describe at least one method of detecting and/or quantifying and/or adjusting for publication bias in meta-analyses. A dedicated data extraction form is developed and pilot-tested. Working in teams of two, we will independently extract relevant information from each eligible article. As this will be a qualitative systematic review, data reporting will involve a descriptive summary. DISCUSSION: Results are expected to be publicly available in mid 2013. This systematic review together with the results of other systematic reviews of the OPEN project (To Overcome Failure to Publish Negative Findings) will serve as a basis for the development of future policies and guidelines regarding the assessment and handling of publication bias in meta-analyses.
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Osakemarkkinoilta on jo useiden vuosien ajan julkaistu lukuisia tutkimuksia, joissa on esitetty havaintoja ajallisesta säännönmukaisuudesta osakkeiden hinnoissa, joita ei pystytä selittämään markkinakohtaisilla fundamenteilla. Nämä niin kutsutut kalenterianomaliat esiintyvät tyypillisesti ajallisissa käännepisteissä, kuten vuoden, kuukauden tai viikon vaihtuessa seuraavaksi. Myös erilaisten katkosten, kuten juhlapyhien, kaupankäyntirutiineissa on havaittu aiheuttavan anomalioita. Tutkimuksen tavoitteena oli tutkia osakemarkkinoilla havaittujen kalenterianomalioiden esiintymistä pohjoismaisilla sähkömarkkinoilla. Tutkitut anomaliat olivat viikonpäivä- kuukausi-, kuunvaihde- ja juhlapyhäanomalia. Näiden lisäksi tutkittiin tuottojen käyttäytymistä optioiden erääntymispäivien läheisyydessä. Yksittäisten tuotteiden sijasta tarkastelut suoritettiin sesonki- ja kvartaalituotteista muodostetuilla vuosituotteilla. Testauksessa käytettiin pienimmän neliösumman menetelmää, huomioidenheteroskedastisuuden, autokorrelaation ja multikollineaarisuuden vaikutukset. Pelkkien kalenterimuuttujien lisäksi testit suoritettiin regressiomalleilla, joissa lisäselittäjinä käytettiin spot-hintaa, päästöoikeuden hintaa ja/tai sade-ennusteita. Tarkastelujakso koostui vuosista 1998-2006.
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In this thesis different parameters influencing critical flux in protein ultrafiltration and membrane foul-ing were studied. Short reviews of proteins, cross-flow ultrafiltration, flux decline and criticalflux and the basic theory of Partial Least Square analysis (PLS) are given at the beginning. The experiments were mainly performed using dilute solutions of globular proteins, commercial polymeric membranes and laboratory scale apparatuses. Fouling was studied by flux, streaming potential and FTIR-ATR measurements. Critical flux was evaluated by different kinds of stepwise procedures and by both con-stant pressure and constant flux methods. The critical flux was affected by transmembrane pressure, flow velocity, protein concentration, mem-brane hydrophobicity and protein and membrane charges. Generally, the lowest critical fluxes were obtained at the isoelectric points of the protein and the highest in the presence of electrostatic repulsion between the membrane surface and the protein molecules. In the laminar flow regime the critical flux increased with flow velocity, but not any more above this region. An increase in concentration de-creased the critical flux. Hydrophobic membranes showed fouling in all charge conditionsand, furthermore, especially at the beginning of the experiment even at very low transmembrane pressures. Fouling of these membranes was thought to be due to protein adsorption by hydrophobic interactions. The hydrophilic membranes used suffered more from reversible fouling and concentration polarisation than from irreversible foul-ing. They became fouled at higher transmembrane pressures becauseof pore blocking. In this thesis some new aspects on critical flux are presented that are important for ultrafiltration and fractionation of proteins.
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Metastatic melanomas are frequently refractory to most adjuvant therapies such as chemotherapies and radiotherapies. Recently, immunotherapies have shown good results in the treatment of some metastatic melanomas. Immune cell infiltration in the tumor has been associated with successful immunotherapy. More generally, tumor infiltrating lymphocytes (TILs) in the primary tumor and in metastases of melanoma patients have been demonstrated to correlate positively with favorable clinical outcomes. Altogether, these findings suggest the importance of being able to identify, quantify and characterize immune infiltration at the tumor site for a better diagnostic and treatment choice. In this paper, we used Fourier Transform Infrared (FTIR) imaging to identify and quantify different subpopulations of T cells: the cytotoxic T cells (CD8+), the helper T cells (CD4+) and the regulatory T cells (T reg). As a proof of concept, we investigated pure populations isolated from human peripheral blood from 6 healthy donors. These subpopulations were isolated from blood samples by magnetic labeling and purities were assessed by Fluorescence Activated Cell Sorting (FACS). The results presented here show that Fourier Transform Infrared (FTIR) imaging followed by supervised Partial Least Square Discriminant Analysis (PLS-DA) allows an accurate identification of CD4+ T cells and CD8+ T cells (>86%). We then developed a PLS regression allowing the quantification of T reg in a different mix of immune cells (e.g. Peripheral Blood Mononuclear Cells (PBMCs)). Altogether, these results demonstrate the sensitivity of infrared imaging to detect the low biological variability observed in T cell subpopulations.
Identification-commitment inventory (ICI-Model): confirmatory factor analysis and construct validity
Resumo:
The aim of this study is to confirm the factorial structure of the Identification-Commitment Inventory (ICI) developed within the frame of the Human System Audit (HSA) (Quijano et al. in Revist Psicol Soc Apl 10(2):27-61, 2000; Pap Psicól Revist Col Of Psicó 29:92-106, 2008). Commitment and identification are understood by the HSA at an individual level as part of the quality of human processes and resources in an organization; and therefore as antecedents of important organizational outcomes, such as personnel turnover intentions, organizational citizenship behavior, etc. (Meyer et al. in J Org Behav 27:665-683, 2006). The theoretical integrative model which underlies ICI Quijano et al. (2000) was tested in a sample (N = 625) of workers in a Spanish public hospital. Confirmatory factor analysis through structural equation modeling was performed. Elliptical least square solution was chosen as estimator procedure on account of non-normal distribution of the variables. The results confirm the goodness of fit of an integrative model, which underlies the relation between Commitment and Identification, although each one is operatively different.
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The classical theory of collision induced emission (CIE) from pairs of dissimilar rare gas atoms was developed in Paper I [D. Reguera and G. Birnbaum, J. Chem. Phys. 125, 184304 (2006)] from a knowledge of the straight line collision trajectory and the assumption that the magnitude of the dipole could be represented by an exponential function of the inter-nuclear distance. This theory is extended here to deal with other functional forms of the induced dipole as revealed by ab initio calculations. Accurate analytical expression for the CIE can be obtained by least square fitting of the ab initio values of the dipole as a function of inter-atomic separation using a sum of exponentials and then proceeding as in Paper I. However, we also show how the multi-exponential fit can be replaced by a simpler fit using only two analytic functions. Our analysis is applied to the polar molecules HF and HBr. Unlike the rare gas atoms considered previously, these atomic pairs form stable bound diatomic molecules. We show that, interestingly, the spectra of these reactive molecules are characterized by the presence of multiple peaks. We also discuss the CIE arising from half collisions in excited electronic states, which in principle could be probed in photo-dissociation experiments.
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OBJECTIVE: The objective of this study was to compare posttreatment seizure severity in a phase III clinical trial of eslicarbazepine acetate (ESL) as adjunctive treatment of refractory partial-onset seizures. METHODS: The Seizure Severity Questionnaire (SSQ) was administered at baseline and posttreatment. The SSQ total score (TS) and component scores (frequency and helpfulness of warning signs before seizures [BS]; severity and bothersomeness of ictal movement and altered consciousness during seizures [DS]; cognitive, emotional, and physical aspects of postictal recovery after seizures [AS]; and overall severity and bothersomeness [SB]) were calculated for the per-protocol population. Analysis of covariance, adjusted for baseline scores, estimated differences in posttreatment least square means between treatment arms. RESULTS: Out of 547 per-protocol patients, 441 had valid SSQ TS both at baseline and posttreatment. Mean posttreatment TS for ESL 1200mg/day was significantly lower than that for placebo (2.68 vs 3.20, p<0.001), exceeding the minimal clinically important difference (MCID: 0.48). Mean DS, AS, and SB were also significantly lower with ESL 1200mg/day; differences in AS and SB exceeded the MCIDs. The TS, DS, AS, and SB were lower for ESL 800mg/day than for placebo; only SB was significant (p=0.013). For both ESL arms combined versus placebo, mean scores differed significantly for TS (p=0.006), DS (p=0.031), and SB (p=0.001). CONCLUSIONS: Therapeutic ESL doses led to clinically meaningful, dose-dependent reductions in seizure severity, as measured by SSQ scores. CLASSIFICATION OF EVIDENCE: This study presents Class I evidence that adjunctive ESL (800 and 1200mg/day) led to clinically meaningful, dose-dependent seizure severity reductions, measured by the SSQ.
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This article analyses the impact that innovation expenditure and intrasectoral and intersectoral externalities have on productivity in Spanish firms. While there is an extensive literature analysing the relationship between innovation and productivity, in this particular area there are far fewer studies that examine the importance of sectoral externalities, especially with the focus on Spain. One novelty of the study, which covers the industrial and service sectors, is that we also consider jointly the technology level of the sector in which the firm operates and the firm size. The database used is the Technological Innovation Panel, PITEC, which includes 12,813 firms for the year 2008 and has been little used in this type of study. The estimation method used is Iteratively Reweighted Least Squares method, IRLS, which is very useful for obtaining robust estimations in the presence of outliers. The results confirm that innovation has a positive effect on productivity, especially in high-tech and large firms. The impact of externalities is more heterogeneous because, while intrasectoral externalities have a poitive and significant effect, especially in low-tech firms independently of size, intersectoral externalities have a more ambiguous effect, being clearly significant for advanced industries in which size has a positive effect.
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EPR users often face the problem of extracting information from frequently low-resolution and complex EPR spectra. Simulation programs that provide a series of parameters, characteristic of the investigated system, have been used to achieve this goal. This work describes the general aspects of one of those programs, the NLSL program, used to fit EPR spectra applying a nonlinear least squares method. Several motion regimes of the probes are included in this computational tool, covering a broad range of spectral changes. The meanings of the different parameters and rotational diffusion models are discussed. The anisotropic case is also treated by including an orienting potential and order parameters. Some examples are presented in order to show its applicability in different systems.
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One hundred fifteen cachaça samples derived from distillation in copper stills (73) or in stainless steels (42) were analyzed for thirty five itens by chromatography and inductively coupled plasma optical emission spectrometry. The analytical data were treated through Factor Analysis (FA), Partial Least Square Discriminant Analysis (PLS-DA) and Quadratic Discriminant Analysis (QDA). The FA explained 66.0% of the database variance. PLS-DA showed that it is possible to distinguish between the two groups of cachaças with 52.8% of the database variance. QDA was used to build up a classification model using acetaldehyde, ethyl carbamate, isobutyl alcohol, benzaldehyde, acetic acid and formaldehyde as chemical descriptors. The model presented 91.7% of accuracy on predicting the apparatus in which unknown samples were distilled.
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The concentration of 15 polycyclic aromatic hydrocarbons (PAHs) in 57 samples of distillates (cachaça, rum, whiskey, and alcohol fuel) has been determined by HPLC-Fluorescence detection. The quantitative analytical profile of PAHs treated by Partial Least Square - Discriminant Analysis (PLS-DA) provided a good classification of the studied spirits based on their PAHs content. Additionally, the classification of the sugar cane derivatives according to the harvest practice was obtained treating the analytical data by Linear Discriminant Analysis (LDA), using naphthalene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benz[a]anthracene, benz[b]fluoranthene, and benz[g,h,i]perylene, as a chemical descriptors.
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The Michaelis-Menten equation is used in many biochemical and bioinorganic kinetic studies involving homogeneous catalysis. Otherwise, it is known that determination of Michaelis-Menten parameters K M, Vmax, and k cat by the well-known Lineweaver-Burk double reciprocal linear equation does not produce the best values for these parameters. In this paper we present a discussion on different linear equations which can be used to calculate these parameters and we compare their results with the values obtained by the more reliable nonlinear least-square fit.
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Genetic algorithm and multiple linear regression (GA-MLR), partial least square (GA-PLS), kernel PLS (GA-KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlation between retention index (RI) and descriptors for 116 diverse compounds in essential oils of six Stachys species. The correlation coefficient LGO-CV (Q²) between experimental and predicted RI for test set by GA-MLR, GA-PLS, GA-KPLS and L-M ANN was 0.886, 0.912, 0.937 and 0.964, respectively. This is the first research on the QSRR of the essential oil compounds against the RI using the GA-KPLS and L-M ANN.