The use of correlation and regression methods in optometry

Correlation and regression are two of the statistical procedures most widely used by optometrists. However, these tests are often misused or interpreted incorrectly, leading to erroneous conclusions from clinical experiments. This review examines the major statistical tests concerned with correlation and regression that are most likely to arise in clinical investigations in optometry. First, the use, interpretation and limitations of Pearson's product moment correlation coefficient are described. Second, the least squares method of fitting a linear regression to data and for testing how well a regression line fits the data are described. Third, the problems of using linear regression methods in observational studies, if there are errors associated in measuring the independent variable and for predicting a new value of Y for a given X, are discussed. Finally, methods for testing whether a non-linear relationship provides a better fit to the data and for comparing two or more regression lines are considered.

Statnote 14: the correlation of two variables (Pearson's 'r')

Pearson's correlation coefficient (‘r’) is one of the most widely used of all statistics. Nevertheless, care needs to be used in interpreting the results because with large numbers of observations, quite small values of ‘r’ become significant and the X variable may only account for a small proportion of the variance in Y. Hence, ‘r squared’ should always be calculated and included in a discussion of the significance of ‘r’. The use of ‘r’ also assumes that the data follow a bivariate normal distribution (see Statnote 17) and this assumption should be examined prior to the study. If the data do not conform to such a distribution, the use of a non-parametric correlation coefficient should be considered. A significant correlation should not be interpreted as indicating ‘causation’ especially in observational studies, in which the two variables may be correlated because of their mutual correlations with other confounding variables.

Statnote 15: the non-parametric correlation coefficients

If in a correlation test, one or both variables are small whole numbers, scores based on a limited scale, or percentages, a non-parametric correlation coefficient should be considered as an alternative to Pearson’s ‘r’. Kendall’s t and Spearman’s rs are similar tests but the former should be considered if the analysis is to be extended to include partial correlations. If the data contain many tied values, then gamma should be considered as a suitable test.

Data analysis methods in optometry. Part 5: correlation

1. Pearson's correlation coefficient only tests whether the data fit a linear model. With large numbers of observations, quite small values of r become significant and the X variable may only account for a minute proportion of the variance in Y. Hence, the value of r squared should always be calculated and included in a discussion of the significance of r. 2. The use of r assumes that a bivariate normal distribution is present and this assumption should be examined prior to the study. If Pearson's r is not appropriate, then a non-parametric correlation coefficient such as Spearman's rs may be used. 3. A significant correlation should not be interpreted as indicating causation especially in observational studies in which there is a high probability that the two variables are correlated because of their mutual correlations with other variables. 4. In studies of measurement error, there are problems in using r as a test of reliability and the ‘intra-class correlation coefficient’ should be used as an alternative. A correlation test provides only limited information as to the relationship between two variables. Fitting a regression line to the data using the method known as ‘least square’ provides much more information and the methods of regression and their application in optometry will be discussed in the next article.

A Study on the Correlation of Bivariate And Trivariate Normal Models

Suppose two or more variables are jointly normally distributed. If there is a common relationship between these variables it would be very important to quantify this relationship by a parameter called the correlation coefficient which measures its strength, and the use of it can develop an equation for predicting, and ultimately draw testable conclusion about the parent population. This research focused on the correlation coefficient ρ for the bivariate and trivariate normal distribution when equal variances and equal covariances are considered. Particularly, we derived the maximum Likelihood Estimators (MLE) of the distribution parameters assuming all of them are unknown, and we studied the properties and asymptotic distribution of . Showing this asymptotic normality, we were able to construct confidence intervals of the correlation coefficient ρ and test hypothesis about ρ. With a series of simulations, the performance of our new estimators were studied and were compared with those estimators that already exist in the literature. The results indicated that the MLE has a better or similar performance than the others.

G7 Stock Markets: Who is The First to Defeat The DCCA Correlation?

Following the methodology of Ferreira and Dionísio (2016), the objective of this paper is to analyze the behavior stock markets in the G7 countries and find which of those countries is the first to reach levels of long-range correlations that are not significant. We carry out this analysis using detrended cross-correlation analysis and its correlation coefficient, to check for the existence of long-range dependence in time series. The existence of long-range dependence could be understood as a possibility of EMH violation. This analysis remains interesting because studies are not conclusive about the existence or not of long memory in stock return rates.

A Highly Improved Method For Sensitive Determination Of Amitriptyline In Pharmaceutical Formulations Using An Unmodified Carbon Nanotube Electrode In The Presence Of Sulfuric Acid.

The present paper describes a novel, simple and reliable differential pulse voltammetric method for determining amitriptyline (AMT) in pharmaceutical formulations. It has been described for many authors that this antidepressant is electrochemically inactive at carbon electrodes. However, the procedure proposed herein consisted in electrochemically oxidizing AMT at an unmodified carbon nanotube paste electrode in the presence of 0.1 mol L(-1) sulfuric acid used as electrolyte. At such concentration, the acid facilitated the AMT electroxidation through one-electron transfer at 1.33 V vs. Ag/AgCl, as observed by the augmentation of peak current. Concerning optimized conditions (modulation time 5 ms, scan rate 90 mV s(-1), and pulse amplitude 120 mV) a linear calibration curve was constructed in the range of 0.0-30.0 μmol L(-1), with a correlation coefficient of 0.9991 and a limit of detection of 1.61 μmol L(-1). The procedure was successfully validated for intra- and inter-day precision and accuracy. Moreover, its feasibility was assessed through analysis of commercial pharmaceutical formulations and it has been compared to the UV-vis spectrophotometric method used as standard analytical technique recommended by the Brazilian Pharmacopoeia.

Feasibility And Reproducibility Of Diffusion-weighted Magnetic Resonance Imaging Of The Fetal Brain In Twin-twin Transfusion Syndrome.

The aim of this study is to test the feasibility and reproducibility of diffusion-weighted magnetic resonance imaging (DW-MRI) evaluations of the fetal brains in cases of twin-twin transfusion syndrome (TTTS). From May 2011 to June 2012, 24 patients with severe TTTS underwent MRI scans for evaluation of the fetal brains. Datasets were analyzed offline on axial DW images and apparent diffusion coefficient (ADC) maps by two radiologists. The subjective evaluation was described as the absence or presence of water diffusion restriction. The objective evaluation was performed by the placement of 20-mm(2) circular regions of interest on the DW image and ADC maps. Subjective interobserver agreement was assessed by the kappa correlation coefficient. Objective intraobserver and interobserver agreements were assessed by proportionate Bland-Altman tests. Seventy-four DW-MRI scans were performed. Sixty of them (81.1%) were considered to be of good quality. Agreement between the radiologists was 100% for the absence or presence of diffusion restriction of water. For both intraobserver and interobserver agreement of ADC measurements, proportionate Bland-Altman tests showed average percentage differences of less than 1.5% and 95% CI of less than 18% for all sites evaluated. Our data demonstrate that DW-MRI evaluation of the fetal brain in TTTS is feasible and reproducible.

Neck Circumference As A New Anthropometric Indicator For Prediction Of Insulin Resistance And Components Of Metabolic Syndrome In Adolescents: Brazilian Metabolic Syndrome Study.

To evaluate the correlation between neck circumference and insulin resistance and components of metabolic syndrome in adolescents with different adiposity levels and pubertal stages, as well as to determine the usefulness of neck circumference to predict insulin resistance in adolescents. Cross-sectional study with 388 adolescents of both genders from ten to 19 years old. The adolescents underwent anthropometric and body composition assessment, including neck and waist circumferences, and biochemical evaluation. The pubertal stage was obtained by self-assessment, and the blood pressure, by auscultation. Insulin resistance was evaluated by the Homeostasis Model Assessment-Insulin Resistance. The correlation between two variables was evaluated by partial correlation coefficient adjusted for the percentage of body fat and pubertal stage. The performance of neck circumference to identify insulin resistance was tested by Receiver Operating Characteristic Curve. After the adjustment for percentage body fat and pubertal stage, neck circumference correlated with waist circumference, blood pressure, triglycerides and markers of insulin resistance in both genders. The results showed that the neck circumference is a useful tool for the detection of insulin resistance and changes in the indicators of metabolic syndrome in adolescents. The easiness of application and low cost of this measure may allow its use in Public Health services.

Intraductal Carcinoma Of The Prostate: Interobserver Reproducibility Survey Of 39 Urologic Pathologists.

The diagnosis of intraductal carcinoma (IDC) of the prostate remains subjective because 3 sets of diagnostic criteria are in use. An internet survey was compiled from 38 photomicrographs showing duct proliferations: 14 signed out as high-grade prostatic intraepithelial neoplasia (HGPIN), 17 IDC, and 7 invasive cribriform/ductal carcinoma. Each image was assessed for the presence of 9 histologic criteria ascribed to IDC. Thirty-nine respondents were asked to rate images as (1) benign/reactive, (2) HGPIN, (3) borderline between HGPIN and IDC, (4) IDC, or (5) invasive cribriform/ductal carcinoma. Intraclass correlation coefficient was 0.68. There was 70% overall agreement with HGPIN, 43% with IDC, and 73% with invasive carcinoma (P < .001, χ(2)). Respondents considered 19 (50%) of 38 cases as IDC candidates, of which 5 (26%) had a two-thirds consensus for IDC; two-thirds consensus for either borderline or IDC was reached in 9 (47%). Two-thirds consensus other than IDC was reached in the remaining 19 of 38 cases, with 15 supporting HGPIN and 4 supporting invasive carcinoma. Findings that differed across diagnostic categories were lumen-spanning neoplastic cells (P < .001), 2× benign duct diameters (P < .001), duct space contours (round, irregular, and branched) (P < .001), papillary growth (P = .048), dense cribriform or solid growth (both P = .023), and comedonecrosis (P = .015). When the 19 of 38 images that attained consensus for HGPIN or invasive carcinoma were removed from consideration, lack of IDC consensus was most often attributable to only loose cribriform growth (5/19), central nuclear maturation (5/19), or comedonecrosis (3/19). Of the 9 histologic criteria, only 1 retained significant correlation with a consensus diagnosis of IDC: the presence of solid areas (P = .038). One case that attained IDC consensus had less than 2× duct enlargement yet still had severe nuclear atypia and nucleomegaly. Six fold nuclear enlargement was not significant (P = .083), although no image had both 6× nuclei and papillary or loose cribriform growth: a combination postulated as sufficient criteria for IDC. Finally, 20.5% of respondents agreed that an isolated diagnosis of IDC on needle biopsy warrants definitive therapy, 20.5% disagreed, and 59.0% considered the decision to depend upon clinicopathologic variables. Although IDC diagnosis remains challenging, we propose these criteria: a lumen-spanning proliferation of neoplastic cells in preexisting ducts with a dense cribriform or partial solid growth pattern. Solid growth, in any part of the duct space, emerges as the most reproducible finding to rule in a diagnosis of IDC. Comedonecrosis is a rarer finding, but in most cases, it should rule in IDC. Duct space enlargement to greater than 2× the diameter of the largest, adjacent benign spaces is usually present in IDC, although there may be rare exceptions.

Classification Of Frankfurters By Ft-raman Spectroscopy And Chemometric Methods.

Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.

The Environment Of Professional Practice And Burnout In Nurses In Primary Healthcare.

to assess how nurses perceive autonomy, control over the environment, the professional relationship between nurses and physicians and the organizational support and correlate them with burnout, satisfaction at work, quality of work and the intention to quit work in primary healthcare. cross-sectional and correlation study, using a sample of 198 nurses. The tools used were the Nursing Work Index Revised, Maslach Burnout Inventory and a form to characterize the nurses. To analyze the data, descriptive statistics were applied and Spearman's correlation coefficient was used. the nurses assessed that the environment is partially favorable for: autonomy, professional relationship and organizational support and that the control over this environment is limited. Significant correlations were evidenced between the Nursing Work Index Revised, Maslach Burnout Inventory and the variables: satisfaction at work, quality of care and the intent to quit the job. the nurses' perceptions regarding the environment of practice are correlated with burnout, satisfaction at work, quality of care and the intent to quit the job. This study provides support for the restructuring of work processes in the primary health care environment and for communication among the health service management, human resources and occupational health areas.

Removal Of Glyphosate Herbicide From Water Using Biopolymer Membranes.

Enormous amounts of pesticides are manufactured and used worldwide, some of which reach soils and aquatic systems. Glyphosate is a non-selective herbicide that is effective against all types of weeds and has been used for many years. It can therefore be found as a contaminant in water, and procedures are required for its removal. This work investigates the use of biopolymeric membranes prepared with chitosan (CS), alginate (AG), and a chitosan/alginate combination (CS/AG) for the adsorption of glyphosate present in water samples. The adsorption of glyphosate by the different membranes was investigated using the pseudo-first order and pseudo-second order kinetic models, as well as the Langmuir and Freundlich isotherm models. The membranes were characterized regarding membrane solubility, swelling, mechanical, chemical and morphological properties. The results of kinetics experiments showed that adsorption equilibrium was reached within 4 h and that the CS membrane presented the best adsorption (10.88 mg of glyphosate/g of membrane), followed by the CS/AG bilayer (8.70 mg of glyphosate/g of membrane). The AG membrane did not show any adsorption capacity for this herbicide. The pseudo-second order model provided good fits to the glyphosate adsorption data on CS and CS/AG membranes, with high correlation coefficient values. Glyphosate adsorption by the membranes could be fitted by the Freundlich isotherm model. There was a high affinity between glyphosate and the CS membrane and moderate affinity in the case of the CS/AG membrane. Physico-chemical characterization of the membranes showed low values of solubility in water, indicating that the membranes are stable and not soluble in water. The SEM and AFM analysis showed evidence of the presence of glyphosate on CS membranes and on chitosan face on CS/AG membranes. The results showed that the glyphosate herbicide can be adsorbed by chitosan membranes and the proposed membrane-based methodology was successfully used to treat a water sample contaminated with glyphosate. Biopolymer membranes therefore potentially offer a versatile method to eliminate agricultural chemicals from water supplies.

Validação de uma bateria de testes de habilidades motoras para atletas de handebol em cadeira de rodas

Universidade Estadual de Campinas . Faculdade de Educação Física

Determinação da velolcidade critica como referencia do limiar anaerobio para o nado costas

Universidade Estadual de Campinas . Faculdade de Educação Física