COVARIATE-ADJUSTED NONPARAMETRIC ANALYSIS OF MAGNETIC RESONANCE IMAGES USING MARKOV CHAIN MONTE CARLO

Permutation tests are useful for drawing inferences from imaging data because of their flexibility and ability to capture features of the brain that are difficult to capture parametrically. However, most implementations of permutation tests ignore important confounding covariates. To employ covariate control in a nonparametric setting we have developed a Markov chain Monte Carlo (MCMC) algorithm for conditional permutation testing using propensity scores. We present the first use of this methodology for imaging data. Our MCMC algorithm is an extension of algorithms developed to approximate exact conditional probabilities in contingency tables, logit, and log-linear models. An application of our non-parametric method to remove potential bias due to the observed covariates is presented.

Direct and Indirect Measures of Capacity Utilization: A Nonparametric Analysis of U.S. Manufacturing

We measure the capacity output of a firm as the maximum amount producible by a firm given a specific quantity of the quasi-fixed input and an overall expenditure constraint for its choice of variable inputs. We compute this indirect capacity utilization measure for the total manufacturing sector in the US as well as for a number of disaggregated industries, for the period 1970-2001. We find considerable variation in capacity utilization rates both across industries and over years within industries. Our results suggest that the expenditure constraint was binding, especially in periods of high interest rates.

Are Indian Firms too Small? A Nonparametric Analysis of Cost Efficiency and Industry Structure of Indian Manufacturing

In this paper we use the 2004-05 Annual Survey of Industries data to estimate the levels of cost efficiency of Indian manufacturing firms in the various states and also get state level measures of industrial organization (IO) efficiency. The empirical results show the presence of considerable cost inefficiency in a majority of the states. Further, we also find that, on average, Indian firms are too small. Consolidating them to attain the optimal scale would further enhance efficiency and lower average cost.

Technical Efficiency in the Indian Textiles Industry: A Nonparametric Analysis of Firm-Level Data

The Indian textiles industry is now at the crossroads with the phasing out of quota regime that prevailed under the Multi-Fiber Agreement (MFA) until the end of 2004. In the face of a full integration of the textiles sector in the WTO, maintaining and enhancing productive efficiency is a precondition for competitiveness of the Indian firms in the new liberalized world market. In this paper we use data obtained from the Annual Survey of Industries for a number of years to measure the levels of technical efficiency in the Indian textiles industry at the firm level. We use both a grand frontier applicable to all firms and a group frontier specific to firms from any individual state, ownership, or organization type in order to evaluate their efficiencies. This permits us to separately identify how locational, proprietary, and organizational characteristics of a firm affect its performance.

Factor analysis and discriminant validity:a brief review of some practical issues

Growth in availability and ability of modern statistical software has resulted in greater numbers of research techniques being applied across the marketing discipline. However, with such advances come concerns that techniques may be misinterpreted by researchers. This issue is critical since misinterpretation could cause erroneous findings. This paper investigates some assumptions regarding: 1) the assessment of discriminant validity; and 2) what confirmatory factor analysis accomplishes. Examples that address these points are presented, and some procedural remedies are suggested based upon the literature. This paper is, therefore, primarily concerned with the development of measurement theory and practice. If advances in theory development are not based upon sound methodological practice, we as researchers could be basing our work upon shaky foundations.

Photoelastic Analysis Of All-on-four Concept Using Different Implants Angulations For Maxilla.

Conventional tilted implants are used in oral rehabilitation for heavily absorbed maxilla to avoid bone grafts; however, few research studies evaluate the biomechanical behavior when different angulations of the implants are used. The aim of this study was evaluate, trough photoelastic method, two different angulations and length of the cantilever in fixed implant-supported maxillary complete dentures. Two groups were evaluated: G15 (distal tilted implants 15°) and G35 (distal tilted implants 35°) n = 6. For each model, 2 distal tilted implants (3.5 x 15 mm long cylindrical cone) and 2 parallel tilted implants in the anterior region (3.5 x 10 mm) were installed. Photoelastic models were submitted to three vertical load tests: in the end of cantilever, in the last pillar and in the all pillars at the same time. We obtained the shear stress by Fringes software and found values for total, cervical and apical stress. The quantitative analysis was performed using the Student tests and Mann-Whitney test; p ≥ 0.05. There is no difference between G15 and G35 for total stress regardless of load type. Analyzing the apical region, G35 reduced strain values considering the distal loads (in the cantilever p = 0.03 and in the last pillar p = 0.02), without increasing the stress level in the cervical region. Considering the load in all pillars, G35 showed higher stress concentration in the cervical region (p = 0.04). For distal loads, G15 showed increase of tension in the apical region, while for load in all pillars, G35 inclination increases stress values in the cervical region.

Escala de autoaceitação para pessoas com cegueira congênita ou precoce : desenvolvimento e investigação psicométrica = Self-acceptance acale for people with congenital or early blindness : development and psychometric analysis

Universidade Estadual de Campinas . Faculdade de Educação Física

Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction

Pattern recognition methods have been successfully applied in several functional neuroimaging studies. These methods can be used to infer cognitive states, so-called brain decoding. Using such approaches, it is possible to predict the mental state of a subject or a stimulus class by analyzing the spatial distribution of neural responses. In addition it is possible to identify the regions of the brain containing the information that underlies the classification. The Support Vector Machine (SVM) is one of the most popular methods used to carry out this type of analysis. The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing discriminative information for the prediction of mental states. The comparison has been carried out using fMRI data from 41 healthy control subjects who participated in two experiments, one involving visual-auditory stimulation and the other based on bimanual fingertapping sequences. The results suggest that MLDA uses significantly more voxels containing discriminative information (related to different experimental conditions) to classify the data. On the other hand, SVM is more parsimonious and uses less voxels to achieve similar classification accuracies. In conclusion, MLDA is mostly focused on extracting all discriminative information available, while SVM extracts the information which is sufficient for classification. (C) 2009 Elsevier Inc. All rights reserved.

Further psychometric study of the Beck Anxiety Inventory including factorial analysis and social anxiety disorder screening

Objective. To analyze the psychometric properties of the Brazilian Portuguese version of the Beck Anxiety Inventory (BAI) in terms of its internal consistency, scores distribution, concurrent and discriminant validity, and factorial analysis in a sample of university students and social anxiety disorder (SAD) cases and non-cases. Methods. A sample of Brazilian university students from the general population (N = 2314) and a sample of university students identified as cases (N = 88) and non-cases (N = 90) of SAD were assessed, using as a parameter the Structured Clinical Interview for the DSM-IV. The different instruments were completed individually in the presence of an experienced rater. Results. The BAI showed adequate internal consistency (0.88-0.92) and discriminant validity, with 0.74 sensitivity and 0.71 specificity for a cut-off score of 10. The factorial analysis suggested a three-factor solution to be the most adequate. Conclusions. The version of the BAI studied is quite adequate to be used in the context of Brazilian university students, identifying the presence of anxiety indicators. However, its usefulness to screen for SAD seems limited.

Analysis of Apical Root Transportation Associated with Protaper Universal F3 and F4 Instruments by Using Digital Subtraction Radiography

Introduction: The aim of this study was to assess the occurrence of apical root transportation after the use of Pro Taper Universal rotary files sizes 3 (F3) and 4 (F4). Methods: Instruments were worked to the apex of the original canal, always by the same operator. Digital subtraction radiography images were produced in buccolingual and mesiodistal projections. A total of 25 radiographs were taken from root canals of human maxillary first molars with curvatures varying from 23-31 degrees. Quantitative data were analyzed by intraclass correlation coefficient and Wilcoxon nonparametric test (P = .05). Results: Buccolingual images revealed a significantly higher degree of apical transportation associated with F4 instruments when compared with F3 instruments in relation to the original canal (Wilcoxon test, P = .007). No significant difference was observed in mesiodistal images (P = .492). Conclusions: F3 instruments should be used with care in curved canals, and F4 instruments should be avoided in apical third preparation of curved canals. (J Endod 2010;36:1052-1055)

Analysis of four gutta-percha techniques used to fill mesial root canals of mandibular molars

P>Aim To compare the percentage of gutta-percha, sealer and voids and the influence of isthmuses in mesial root canals of mandibular molars filled with different techniques. Methodology Canals in 60 mesial roots of mandibular first molars were prepared with ProTaper instruments to size F2 (size 25, 0.08 taper) and filled using a single-cone, lateral compaction, System B or Thermafil techniques. An epoxy resin sealer was labelled with Rhodamine-B dye to allow analysis under a confocal microscope. The percentage of gutta-percha, sealer and area of voids was calculated at 2, 4 and 6 mm from the apex, using Image Tool 3.0 software. Statistical analysis was performed using nonparametric Kruskal-Wallis and Dunn tests (P < 0.05). The influence of isthmuses on the presence or absence of voids was evaluated using the Fisher test. Results At the 2 mm level, the percentage of gutta-percha, sealer and voids was similar amongst the System B, lateral compaction and single-cone techniques. The single-cone technique revealed significantly less gutta-percha, more sealer and voids in comparison with the Thermafil technique at the 2 and 4 mm level (P < 0.05). The analysis of all sections (2, 4 and 6 mm) revealed that more gutta-percha and less sealer and voids were found in root canals filled with Thermafil and System B techniques (P < 0.05). The Fisher test revealed that the presence of isthmuses increased the occurence of voids in the lateral compaction group only (P < 0.05). Conclusion Gutta-percha, sealer filled area and voids were dependent on the canal-filling technique. The presence of isthmuses may influence the quality of root filling.

Survival analysis: a tool in the study of post-harvest diseases in peaches

Survival analysis is applied when the time until the occurrence of an event is of interest. Such data are routinely collected in plant diseases, although applications of the method are uncommon. The objective of this study was to use two studies on post-harvest diseases of peaches, considering two harvests together and the existence of random effect shared by fruits of a same tree, in order to describe the main techniques in survival analysis. The nonparametric Kaplan-Meier method, the log-rank test and the semi-parametric Cox's proportional hazards model were used to estimate the effect of cultivars and the number of days after full bloom on the survival to the brown rot symptom and the instantaneous risk of expressing it in two consecutive harvests. The joint analysis with baseline effect, varying between harvests, and the confirmation of the tree effect as a grouping factor with random effect were appropriate to interpret the phenomenon (disease) evaluated and can be important tools to replace or complement the conventional analysis, respecting the nature of the variable and the phenomenon.

Ensemble classifiers in remote sensing: a comparative analysis

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Nonparametric estimation of time-dependent ROC curves conditional on a continuous covariate

The receiver-operating characteristic (ROC) curve is the most widely used measure for evaluating the performance of a diagnostic biomarker when predicting a binary disease outcome. The ROC curve displays the true positive rate (or sensitivity) and the false positive rate (or 1-specificity) for different cut-off values used to classify an individual as healthy or diseased. In time-to-event studies, however, the disease status (e.g. death or alive) of an individual is not a fixed characteristic, and it varies along the study. In such cases, when evaluating the performance of the biomarker, several issues should be taken into account: first, the time-dependent nature of the disease status; and second, the presence of incomplete data (e.g. censored data typically present in survival studies). Accordingly, to assess the discrimination power of continuous biomarkers for time-dependent disease outcomes, time-dependent extensions of true positive rate, false positive rate, and ROC curve have been recently proposed. In this work, we present new nonparametric estimators of the cumulative/dynamic time-dependent ROC curve that allow accounting for the possible modifying effect of current or past covariate measures on the discriminatory power of the biomarker. The proposed estimators can accommodate right-censored data, as well as covariate-dependent censoring. The behavior of the estimators proposed in this study will be explored through simulations and illustrated using data from a cohort of patients who suffered from acute coronary syndrome.

Nonparametric estimation of the survival function for ordered multivariate failure time data: a comparative study

In longitudinal studies of disease, patients may experience several events through a follow-up period. In these studies, the sequentially ordered events are often of interest and lead to problems that have received much attention recently. Issues of interest include the estimation of bivariate survival, marginal distributions and the conditional distribution of gap times. In this work we consider the estimation of the survival function conditional to a previous event. Different nonparametric approaches will be considered for estimating these quantities, all based on the Kaplan-Meier estimator of the survival function. We explore the finite sample behavior of the estimators through simulations. The different methods proposed in this article are applied to a data set from a German Breast Cancer Study. The methods are used to obtain predictors for the conditional survival probabilities as well as to study the influence of recurrence in overall survival.