Análisis Discriminante mediante SPSS

El análisis discriminante es un método estadístico a través del cual se busca conocer qué variables, medidas en objetos o individuos, explican mejor la atribución de la diferencia de los grupos a los cuales pertenecen dichos objetos o individuos. Es una técnica que nos permite comprobar hasta qué punto las variables independientes consideradas en la investigación clasifican correctamente a los sujetos u objetos. Se muestran y explican los principales elementos que se relacionan con el procedimiento para llevar a cabo el análisis discriminante y su aplicación utilizando el paquete estadístico SPSS, versión 18, para el desarrollo del modelo estadístico, las condiciones para la aplicación del análisis, la estimación e interpretación de las funciones discriminantes, los métodos de clasificación y la validación de los resultados.

Hardness of FRHC-Cu determined by statistical analysis

A statistical indentation method has been employed to study the hardness value of fire-refined high conductivity copper, using nanoindentation technique. The Joslin and Oliver approach was used with the aim to separate the hardness (H) influence of copper matrix, from that of inclusions and grain boundaries. This approach relies on a large array of imprints (around 400 indentations), performed at 150 nm of indentation depth. A statistical study using a cumulative distribution function fit and Gaussian simulated distributions, exhibits that H for each phase can be extracted when the indentation depth is much lower than the size of the secondary phases. It is found that the thermal treatment produces a hardness increase, due to the partly re-dissolution of the inclusions (mainly Pb and Sn) in the matrix.

Probabilistic age classification with Bayesian networks: a study on the ossification status of the medial clavicular epiphysis

In the past few decades, the rise of criminal, civil and asylum cases involving young people lacking valid identification documents has generated an increase in the demand of age estimation. The chronological age or the probability that an individual is older or younger than a given age threshold are generally estimated by means of some statistical methods based on observations performed on specific physical attributes. Among these statistical methods, those developed in the Bayesian framework allow users to provide coherent and transparent assignments which fulfill forensic and medico-legal purposes. The application of the Bayesian approach is facilitated by using probabilistic graphical tools, such as Bayesian networks. The aim of this work is to test the performances of the Bayesian network for age estimation recently presented in scientific literature in classifying individuals as older or younger than 18 years of age. For these exploratory analyses, a sample related to the ossification status of the medial clavicular epiphysis available in scientific literature was used. Results obtained in the classification are promising: in the criminal context, the Bayesian network achieved, on the average, a rate of correct classifications of approximatively 97%, whilst in the civil context, the rate is, on the average, close to the 88%. These results encourage the continuation of the development and the testing of the method in order to support its practical application in casework.

Combining Advanced Forecasting Methods with System Dynamics - the Case of Finnish Seaports

Seaports play an important part in the wellbeing of a nation. Many nations are highly dependent on foreign trade and most trade is done using sea vessels. This study is part of a larger research project, where a simulation model is required in order to create further analyses on Finnish macro logistical networks. The objective of this study is to create a system dynamic simulation model, which gives an accurate forecast for the development of demand of Finnish seaports up to 2030. The emphasis on this study is to show how it is possible to create a detailed harbor demand System Dynamic model with the help of statistical methods. The used forecasting methods were ARIMA (autoregressive integrated moving average) and regression models. The created simulation model gives a forecast with confidence intervals and allows studying different scenarios. The building process was found to be a useful one and the built model can be expanded to be more detailed. Required capacity for other parts of the Finnish logistical system could easily be included in the model.

Avaliação do uso de métodos quimiométricos em análise de solos

One of the major interests in soil analysis is the evaluation of its chemical, physical and biological parameters, which are indicators of soil quality (the most important is the organic matter). Besides there is a great interest in the study of humic substances and on the assessment of pollutants, such as pesticides and heavy metals, in soils. Chemometrics is a powerful tool to deal with these problems and can help soil researchers to extract much more information from their data. In spite of this, the presence of these kinds of strategies in the literature has obtained projection only recently. The utilization of chemometric methods in soil analysis is evaluated in this article. The applications will be divided in four parts (with emphasis in the first two): (i) descriptive and exploratory methods based on Principal Component Analysis (PCA); (ii) multivariate calibration methods (MLR, PCR and PLS); (iii) methods such as Evolving Factor Analysis and SIMPLISMA; and (iv) artificial intelligence methods, such as Artificial Neural Networks.

Classificação de cerâmicas arqueológicas da Bacia Amazônica

In order to elucidate the traditional classification of archaeological artefacts, a multielemental analytical method for characterisation of its micro and macro chemical constituents. combined with statistical multivariate analysis for classification, were used. Instrumental thermal neutron activation analysis, for elemental chemical determination, and three statistical methods: discriminant, cluster and modified cluster analysis were applied. The statistical results obtained for the samples from Iquiri, Quinari and Xapuri archaeological phases were in good agreement with the conventional archaeological classification. Iaco and Jacuru archaeological phase were not characterised as homogenous groups. Iquiri phase were the most distinct in relation to the other analysed groups. An homogeneous group for 54% collected samples at the Los Angeles site was also found, this could be characterised as a new archaeological phase.

Análisis composicional de datos en Ciencias Geoambientales

Compositional data (concentrations) are common in geosciences. Neglecting its character mey lead to erroneous conclusions. Spurious correlation (K. Pearson, 1897) has disastrous consequences. On the basis of the pioneering work by J. Aitchison in the 1980s, a methodology free of these drawbacks is now available. The geometry of the símplex allows the representation of compositions using orthogonal co-ordinares, to which usual statistical methods can be applied, thus facilating computation ans analysis. The use of (log) ratios precludes the interpretation of single concentrations disregarding their relative character. A hydro-chemical data set is used to illustrate the point

The adequacy of different robust statistical tests in comparing two independent groups

In the current study, we evaluated various robust statistical methods for comparing two independent groups. Two scenarios for simulation were generated: one of equality and another of population mean differences. In each of the scenarios, 33 experimental conditions were used as a function of sample size, standard deviation and asymmetry. For each condition, 5000 replications per group were generated. The results obtained by this study show an adequate type error I rate but not a high power for the confidence intervals. In general, for the two scenarios studied (mean population differences and not mean population differences) in the different conditions analysed, the Mann-Whitney U-test demonstrated strong performance, and a little worse the t-test of Yuen-Welch.

Estatística aplicada à química: dez dúvidas comuns

Ten common doubts of chemistry students and professionals about their statistical applications are discussed. The use of the N-1 denominator instead of N is described for the standard deviation. The statistical meaning of the denominators of the root mean square error of calibration (RMSEC) and root mean square error of validation (RMSEV) are given for researchers using multivariate calibration methods. The reason why scientists and engineers use the average instead of the median is explained. Several problematic aspects about regression and correlation are treated. The popular use of triplicate experiments in teaching and research laboratories is seen to have its origin in statistical confidence intervals. Nonparametric statistics and bootstrapping methods round out the discussion.

UV determination of epinephrine, uric acid, and acetaminophen in pharmaceutical formulations and some human body fluids using multivariate calibration

In this work, a spectrophotometric methodology was applied in order to determine epinephrine (EP), uric acid (UA), and acetaminophen (AC) in pharmaceutical formulations and spiked human serum, plasma, and urine by using a multivariate approach. Multivariate calibration methods such as partial least squares (PLS) methods and its derivates were used to obtain a model for simultaneous determination of EP, UA and AC with good figures of merit and mixture design was in the range of 1.8 - 35.3, 1.7 - 16.8, and 1.5 - 12.1 µg mL-1. The 2nd derivate PLS showed recoveries of 95.3 - 103.3, 93.3 - 104.0, and 94.0 - 105.5 µg mL-1 for EP, UA, and AC, respectively.

Mental Well-being at Work. A Sign of a Healthy Organisation and a Necessary Precondition for Organisational Development

One of the aims of the study was to clarify the reliability and validity of the Job Diagnostic Survey (JDS) and the Eigenzustand (EZ) method as measures of the objective characteristics of work and short-term mental work load in the Finnish data. The reliability and validity were examined taking into consideration the theoretical backgrounds of the methods and the reliability of the measurements. The methods were used for finding out the preconditions for organisational development based on self-improvement and clarifying the impacts of working environment (organisational functioning and job characteristics) on a worker’s mental state and health. The influences were examined on a general level - regardless of individual personal or specific contextual factors. One aim was also to clarify how cognitions and emotions are intertwined and how they influence a person’s perception of the working environment. The data consisted of 15 blue-collar organisations in the public sector. The organisations were divided in target and comparison groups depending on the research frames. The data was collected by questionnaires by post. The exploratory and confirmatory factor analyses (Lisrel) were used as the main statistical methods in examining the structures of the methods and impacts between the variables. It was shown that it is possible for organisations to develop their working conditions themselves on specific preconditions. The advance of the development processes could be shown by the amount of the development activity as well as by the changes of the mental well-being (ability to act) and sick absenteeism of the personnel. It was found that the JDS and the EZ methods were reliable and valid measures in the Finnish data. It was shown that, in addition to the objective working environment (organisational functioning and job characteristics), also such a personal factor as selfesteem influences a person’s perception of mental work load. However, the influence did not seem to be direct. The importance of job satisfaction as a general indicator of perceived working conditions was emphasised. Emotional and cognitive factors were found to be functionally intertwined constituting a common factor. Organisational functioning and the characteristics of work had connections with a person’s health measured by sick absenteeism.

University Image vs. University Identity: Congruence between Expectations and Experience

The aim of this thesis was to examine congruencies between university identity and university images of prospective and current students. Therefore, factors essentially influencing on expected and experienced university images were identified. Providing an understanding on the differences in the formation of both concepts allowed the analysis of potential incongruities between a university’s identity and the perceptions its students hold. The study was conducted in July and August 2013 at Lappeenranta University of Technology by means of a web-based research survey. The sample consisted of 160 international Master’s degree students who were admitted in 2011, 2012 and 2013. Descriptive and multivariate statistical analysis methods were used to process the data. The results of the study indicated statistically significant incongruities between the case university’s identity and its students’ images. Further, the expected and experienced university images showed incongruities to each other. Deviations were additionally detected to be dependent on the students’ home regions. All in all, there is potential for an improvement of the students’ experiences resulting from a low perception of the student’s preparation for future job life.

Hoitotyön koulutuksen opiskelijavalinnat. Seurantatutkimus kahden valintakoemenetelmän yhteydestä opiskelijoiden osaamiseen ja opiskelumotivaatioon

Hoitotyön koulutukseen pyritään valitsemaan alalle soveltuvia, motivoituneita sekä teoreettisissa ja kliinisissä opinnoissa menestyviä opiskelijoita. Tämän seurantatutkimuksen tarkoituksena oli vertailla soveltuvuuskokeella ja kirjallisella kokeella valittujen hoitotyön opiskelijoiden osaamista ja opiskelumotivaatiota. Tutkimuksen tavoitteena oli tehdä tutkimustulosten perusteella hoitotyön koulutuksen opiskelijavalintoihin liittyviä kehittämisehdotuksia. Tutkimuksen kohderyhmänä olivat yhteen ammattikorkeakouluun syksyn 2002 ja syksyn 2004 välisenä aikana hoitotyön koulutukseen kahdella eri valintakoemenetelmällä valitut hoitotyön opiskelijat (N=626) (sairaanhoitotyö, terveydenhoitotyö, kätilötyö). Opiskelijaryhmistä muodostettiin kaksi kohorttia valintakoemenetelmän perusteella: soveltuvuuskoe (VAL1, N=368) ja kirjallinen koe (VAL2, N=258). Seurantatutkimuksen aineisto kerättiin opiskelijoiden opintorekisteristä sekä kahdella strukturoidulla mittarilla, joilla kartoitettiin hoitotyön opiskelijoiden itsearvioitua hoitotyön osaamista (OSAA-mittari) ja opiskelumotivaatiota (MOTI-mittari). Seurantatutkimuksen aineistonkeruu ajoittui opiskelijoiden kolmannelle lukukaudella (1. mittaus, 2004‒2006, VAL1 n=234, VAL2 n=126) ja valmistumisvaiheeseen (2. mittaus, 2006‒2009, VAL1 n=149, VAL2 n=108). Ensimmäisen mittauksen vastausprosentti oli 75,0 % ja toisen mittauksen 92,4 %. Aineistojen analysoinnissa käytettiin pitkittäistutkimukseen soveltuvia monimuuttujamenetelmiä. Kahdella valintakoemenetelmällä valikoitui pienistä eroista huolimatta osaamiseltaan ja opiskelumotivaatioltaan hyvin samanlaisia opiskelijoita. Soveltuvuuskokeella valitut opiskelijat kokivat ryhmän kannustavuuden vahvemmaksi valmistumisvaiheessa kuin kirjallisella kokeella valitut. Kirjallisella kokeella valittujen opiskelijoiden kolmannen lukukauden arvosanoihin perustuva osaaminen oli parempaa kuin soveltuvuuskokeella valittujen opiskelijoiden. Suuntautumisvaihtoehto, hoitoalan työkokemus, peruskoulutus ja hakusija olivat merkittävimmin yhteydessä opiskelijoiden osaamiseen ja opiskelumotivaatioon. Valintakoemenetelmä selitti eniten opiskelijoiden osaamisessa ja opiskelumotivaatiossa ilmenneitä eroja, joskin selitysosuudet jäivät alhaisiksi. Kehittämisehdotukset kohdistuvat valintakoemenetelmien kehittämiseen ja säännölliseen arviointiin sekä alalle motivoituneisuuden määrittelyyn ja mittaamisen kehittämiseen. Jatkotutkimusaiheina ehdotetaan eri valintakoemenetelmien testaamista ja tutkimuksessa käytettyjen mittareiden edelleen kehittämistä.

Glomerular damage as a predictor of renal allograft loss

Interstitial fibrosis and tubular atrophy (IF/TA) are the most common cause of renal graft failure. Chronic transplant glomerulopathy (CTG) is present in approximately 1.5-3.0% of all renal grafts. We retrospectively studied the contribution of CTG and recurrent post-transplant glomerulopathies (RGN) to graft loss. We analyzed 123 patients with chronic renal allograft dysfunction and divided them into three groups: CTG (N = 37), RGN (N = 21), and IF/TA (N = 65). Demographic data were analyzed and the variables related to graft function identified by statistical methods. CTG had a significantly lower allograft survival than IF/TA. In a multivariate analysis, protective factors for allograft outcomes were: use of angiotensin-converting enzyme inhibitor (ACEI; hazard ratio (HR) = 0.12, P = 0.001), mycophenolate mofetil (MMF; HR = 0.17, P = 0.026), hepatitis C virus (HR = 7.29, P = 0.003), delayed graft function (HR = 5.32, P = 0.016), serum creatinine ≥1.5 mg/dL at the 1st year post-transplant (HR = 0.20, P = 0.011), and proteinuria ≥0.5 g/24 h at the 1st year post-transplant (HR = 0.14, P = 0.004). The presence of glomerular damage is a risk factor for allograft loss (HR = 4.55, P = 0.015). The presence of some degree of chronic glomerular damage in addition to the diagnosis of IF/TA was the most important risk factor associated with allograft loss since it could indicate chronic active antibody-mediated rejection. ACEI and MMF were associated with better outcomes, indicating that they might improve graft survival.

Exact Tests for Contemporaneous Correlation of Disturbances in Seemingly Unrelated Regressions.

This paper proposes finite-sample procedures for testing the SURE specification in multi-equation regression models, i.e. whether the disturbances in different equations are contemporaneously uncorrelated or not. We apply the technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] to obtain exact tests based on standard LR and LM zero correlation tests. We also suggest a MC quasi-LR (QLR) test based on feasible generalized least squares (FGLS). We show that the latter statistics are pivotal under the null, which provides the justification for applying MC tests. Furthermore, we extend the exact independence test proposed by Harvey and Phillips (1982) to the multi-equation framework. Specifically, we introduce several induced tests based on a set of simultaneous Harvey/Phillips-type tests and suggest a simulation-based solution to the associated combination problem. The properties of the proposed tests are studied in a Monte Carlo experiment which shows that standard asymptotic tests exhibit important size distortions, while MC tests achieve complete size control and display good power. Moreover, MC-QLR tests performed best in terms of power, a result of interest from the point of view of simulation-based tests. The power of the MC induced tests improves appreciably in comparison to standard Bonferroni tests and, in certain cases, outperforms the likelihood-based MC tests. The tests are applied to data used by Fischer (1993) to analyze the macroeconomic determinants of growth.