Associations between two variables, for instance between brain and behavioral measurements, are often studied using correlations, and in particular Pearson correlation. However, Pearson correlation is not robust: outliers can introduce false correlations or mask existing ones. These problems are exacerbated in brain imaging by a widespread lack of control for multiple comparisons, and several i...

It is widely appreciated that many studies in psychological science suffer from low statistical power. One of the consequences analyzing underpowered with thresholds significance a high risk finding exaggerated effect size estimates, right or wrong direction. These inferential risks can be directly quantified terms Type M (magnitude) error and S (sign) error, which communicate design choices on...

Three main approaches on how audio signals can be used as input to a deep learning model are: extracting hand-crafted features from signals, mapping into appropriate images such spectrogram-like ones, and using directly raw signals. Among these approaches, the usage of represents compromise regarding bias enforced by processing (seen in features) computational demands signals). When any is inpu...

Reconstruction of broken fragments is an extremely difficult task, mainly due to the high probability of missing pieces and the likelihood of erosion. This process is tedious and requires many hours to complete even for the experienced archaeologist. This paper describes some of the most successful fragment reconstruction algorithms and presents a new technique for reassembly. The technique rel...

Objective: The aim of present study was to find the effect of cholesterol level on platelet aggregability in normal individuals. Methodology: This study was conducted in Cardiology department, Lady Reading Hospital, Peshawar in SeptemberOctober 2007. Normal individuals aged 18 years or above were randomly included. Patients who were suffering from any cardiovascular or other diseases were exclu...

This chapter first reviews the major consequences of ordinal measurement in Confirmatory Factor Analysis (CFA) models and introduces the reader to the Polychoric correlation coefficient, a measure of association designed to avoid these consequences. Next, it presents the results of a Monte Carlo experiment in which the performance of the estimates of a CFA model based on Pearson and Polychoric ...