17 resultados para Correlation methods
em Aston University Research Archive
Resumo:
To elucidate the structures of orgamc molecules in solution using pulse FT NMR, heteronuclear pulse sequence experiments to probe carbon-13 (13C) and proton (1H) spin systems are invaluable. The one-dimensional insensitive nucleus detected PENDANT experiment finds popular use for structure determination via one-bond 13C-1H scalar couplings. PENDANT facilitates the desired increase in 13C signal-to-noise ratio, and unlike many other pulse sequence experiments (e.g., refocused INEPT and DEPT), allows the simultaneous detection of 13C quaternary nuclei. The tlrst chapter herein details the characterisation of PENDANT and the successful rectification of spectral anomalies that occur when it is used without proton broadband decoupling. Multiple-bond (long-range) l3C-1H scalar coupling correlations can yield important bonding information. When the molecule under scrutiny is devoid of proton spectral crowding, and more sensitive 'inverse' pulse sequence experiments are not available, one may use insensitive nucleus detected long-range selective one-dimensional correlation methods, rather than more time consuming and insensitive multidimensional analogues. To this end a novel long-range selective one-dimensional correlation pulse sequence experiment has been invented. Based on PENDANT, the new experiment is shown to rival the popular selective INEPT technique because it can determine the same correlations while simultaneously detecting isolated 13C quaternary nuclei. INEPT cannot facilitate this, potentially leaving other important quaternary nuclei undetected. The novel sequence has been modified further to yield a second novel experiment that simultaneously yields selective 13C transient nOe data. Consequently, the need to perform the two experiments back-to-back is conveniently removed, and the experimental time reduced. Finally, the SNARE pulse sequence was further developed. SNARE facilitates the reduction of experimental time by accelerating the relaxation of protons upon which pulse sequences, to which SNARE is appended, relies. It is shown, contrary to the original publication, that reiaxation time savings can be derived from negative nOes.
Resumo:
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.
Resumo:
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.
Resumo:
This article reviews the statistical methods that have been used to study the planar distribution, and especially clustering, of objects in histological sections of brain tissue. The objective of these studies is usually quantitative description, comparison between patients or correlation between histological features. Objects of interest such as neurones, glial cells, blood vessels or pathological features such as protein deposits appear as sectional profiles in a two-dimensional section. These objects may not be randomly distributed within the section but exhibit a spatial pattern, a departure from randomness either towards regularity or clustering. The methods described include simple tests of whether the planar distribution of a histological feature departs significantly from randomness using randomized points, lines or sample fields and more complex methods that employ grids or transects of contiguous fields, and which can detect the intensity of aggregation and the sizes, distribution and spacing of clusters. The usefulness of these methods in understanding the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Creutzfeldt-Jakob disease is discussed. © 2006 The Royal Microscopical Society.
Resumo:
The objective of this study was to compare the in vitro dissolution profile of a new rapidly absorbed paracetamol tablet containing sodium bicarbonate (PS) with that of a conventional paracetamol tablet (P), and to relate these by deconvolution and mapping to in vivo release. The dissolution methods used include the standard procedure described in the USP monograph for paracetamol tablets, employing buffer at pH5.8 or 0.05 M HCl at stirrer speeds between 10 and 50 rpm. The mapping process was developed and implemented in Microsoft Excel® worksheets that iteratively calculated the optimal values of scale and shape factors which linked in vivo time to in vitro time. The in vitro-in vivo correlation (IVIVC) was carried out simultaneously for both formulations to produce common mapping factors. The USP method, using buffer at pH5.8, demonstrated no difference between the two products. However, using an acidic medium the rate of dissolution of P but not of PS decreased with decreasing stirrer speed. A significant correlation (r=0.773; p<.00001) was established between in vivo release and in vitro dissolution using the profiles obtained with 0.05 M HCl and a stirrer speed of 30 rpm. The scale factor for optimal simultaneous IVIVC in the fasting state was 2.54 and the shape factor was 0.16; corresponding values for mapping in the fed state were 3.37 and 0.13 (implying a larger in vitro-in vivo time difference but reduced shape difference in the fed state). The current IVIVC explains, in part, the observed in vivo variability of the two products. The approach to mapping may also be extended to different batches of these products, to predict the impact of any changes of in vitro dissolution on in vivo release and plasma drug concentration-time profiles.
Resumo:
Histological features visible in thin sections of brain tissue, such as neuronal perikarya, blood vessels, or pathological lesions may exhibit a degree of spatial association or correlation. In neurodegenerative disorders such as AD, Pick's disease, and CJD, information on whether different types of pathological lesion are spatially correlated may be useful in elucidating disease pathogenesis. In the present article the statistical methods available for studying spatial association in histological sections are reviewed. These include tests of interspecific association between two or more histological features using χ2 contingency tables, measurement of 'complete' and 'absolute' association, and more complex methods that use grids of contiguous samples. In addition, the use of correlation matrices and stepwise multiple regression methods are described. The advantages and limitations of each method are reviewed and possible future developments discussed.
Resumo:
Aim: To investigate the correlation between tests of visual function and perceived visual ability recorded with a quality of life questionnaire for patients with uveitis. Methods: 132 patients with various types of uveitis were studied. High (monocular and binocular) and low (binocular) contrast logMAR letter acuities were recorded using a Bailey-Lovie chart. Contrast sensitivity (binocular) was determined using a Pelli-Robson chart. Vision related quality of life was assessed using the Vision Specific Quality of Life (VQOL) questionnaire. Results: VQOL declined with reduced performance on the following tests: binocular high contrast visual acuity (p = 0.0011), high contrast visual acuity of the better eye (p = 0.0012), contrast sensitivity (p = 0.005), binocular low contrast visual acuity (p = 0.0065), and high contrast visual acuity of the worse eye (p = 0.015). Stepwise multiple regression analysis revealed binocular high contrast visual acuity (p <0.01) to be the only visual function adequate to predict VQOL. The age of the patient was also significantly associated with perceived visual ability (p <0.001). Conclusions: Binocular high contrast visual acuity is a good measure of how uveitis patients perform in real life situations. Vision quality of life is worst in younger patients with poor binocular visual acuity.
Resumo:
The pathological lesions characteristic of Alzheimer's disease (AD), viz., senile plaques (SP) and neurofibrillary tangles (NFT) may not be randomly distributed with reference to each other but exhibit a degree of sptial association or correlation, information on the degree of association between SP and NFT or between the lesions and normal histological features, such as neuronal perikarya and blood vessels, may be valuable in elucidating the pathogenesis of AD. This article reviews the statistical methods available for studying the degree of spatial association in histological sections of AD tissue. These include tests of interspecific association between two or more histological features using chi-square contingency tables, measurement of 'complete' and 'absolute' association, and more complex methods that use grids of contiguous samples. In addition, analyses of association using correlation matrices and stepwise multiple regression methods are described. The advantages and limitations of each method are reviewed and possible future developments discussed.
Resumo:
Counts of Pick bodies (PB), Pick cells (PC), senile plaques (SP) and neurofibrillary tangles (NFT) were made in the frontal and temporal cortex from patients with Pick's disease (PD). Lesions were stained histologically with hematoxylin and eosin (HE) and the Bielschowsky silver impregnation method and labeled immunohistochemically with antibodies raised to ubiquitin and tau. The greatest numbers of PB were revealed by immunohistochemistry. Counts of PB revealed by ubiquitin and tau were highly positively correlated which suggested that the two antibodies recognized virtually identical populations of PB. The greatest numbers of PC were revealed by HE followed by the anti-ubiquitin antibody. However, the correlation between counts was poor, suggesting that HE and ubiquitin revealed different populations of PC. The greatest numbers of SP and NFT were revealed by the Bielschowsky method indicating the presence of Alzheimer-type lesions not revealed by the immunohistochemistry. In addition, more NFT were revealed by the anti-ubiquitin compared with the anti-tau antibody. The data suggested that in PD: (i) the anti-ubiquitin and anti-tau antibodies were equally effective at labeling PB; (ii) both HE and anti-ubiquitin should be used to quantitate PC; and (iii) the Bielschowsky method should be used to quantitate SP and NFT.
Resumo:
1. Fitting a linear regression to data provides much more information about the relationship between two variables than a simple correlation test. A goodness of fit test of the line should always be carried out. Hence, r squared estimates the strength of the relationship between Y and X, ANOVA whether a statistically significant line is present, and the ‘t’ test whether the slope of the line is significantly different from zero. 2. Always check whether the data collected fit the assumptions for regression analysis and, if not, whether a transformation of the Y and/or X variables is necessary. 3. If the regression line is to be used for prediction, it is important to determine whether the prediction involves an individual y value or a mean. Care should be taken if predictions are made close to the extremities of the data and are subject to considerable error if x falls beyond the range of the data. Multiple predictions require correction of the P values. 3. If several individual regression lines have been calculated from a number of similar sets of data, consider whether they should be combined to form a single regression line. 4. If the data exhibit a degree of curvature, then fitting a higher-order polynomial curve may provide a better fit than a straight line. In this case, a test of whether the data depart significantly from a linear regression should be carried out.
Resumo:
The last decade has seen a considerable increase in the application of quantitative methods in the study of histological sections of brain tissue and especially in the study of neurodegenerative disease. These disorders are characterised by the deposition and aggregation of abnormal or misfolded proteins in the form of extracellular protein deposits such as senile plaques (SP) and intracellular inclusions such as neurofibrillary tangles (NFT). Quantification of brain lesions and studying the relationships between lesions and normal anatomical features of the brain, including neurons, glial cells, and blood vessels, has become an important method of elucidating disease pathogenesis. This review describes methods for quantifying the abundance of a histological feature such as density, frequency, and 'load' and the sampling methods by which quantitative measures can be obtained including plot/quadrat sampling, transect sampling, and the point-quarter method. In addition, methods for determining the spatial pattern of a histological feature, i.e., whether the feature is distributed at random, regularly, or is aggregated into clusters, are described. These methods include the use of the Poisson and binomial distributions, pattern analysis by regression, Fourier analysis, and methods based on mapped point patterns. Finally, the statistical methods available for studying the degree of spatial correlation between pathological lesions and neurons, glial cells, and blood vessels are described.
Resumo:
This thesis set out to develop an objective analysis programme that correlates with subjective grades but has improved sensitivity and reliability in its measures so that the possibility of early detection and reliable monitoring of changes in anterior ocular surfaces (bulbar hyperaemia, palpebral redness, palpebral roughness and corneal straining) could be increased. The sensitivity of the program was 20x greater than subjective grading by optometrists. The reliability was found to be optimal (r=1.0) with subjective grading up to 144x more variable (r=0.08). Objective measures were used to create formulae for an overall ‘objective-grade’ (per surface) equivalent to those displayed by the CCLRU or Efron scales. The correlation between the formulated objective verses subjective grades was high, with adjusted r2 up to 0.96. Determination of baseline levels of objective grade were investigated over four age groups (5-85years n= 120) so that in practice a comparison against the ‘normal limits’ could be made. Differences for bulbar hyperaemia were found between the age groups (p<0.001), and also for palpebral redness and roughness (p<0.001). The objective formulae were then applied to the investigation of diurnal variation in order to account for any change that may affect the baseline. Increases in bulbar hyperaemia and palpebral redness were found between examinations in the morning and evening. Correlation factors were recommended. The program was then applied to clinical situations in the form of a contact lens trial and an investigation into iritis and keratoconus where it successfully recognised various surface changes. This programme could become a valuable tool, greatly improving the chances of early detection of anterior ocular abnormalities, and facilitating reliable monitoring of disease progression in clinical as well as research environments.
Resumo:
Lipid peroxidation products like malondialdehyde, 4-hydroxynonenal and F(2)-isoprostanes are widely used as markers of oxidative stress in vitro and in vivo. This study reports the results of a multi-laboratory validation study by COST Action B35 to assess inter-laboratory and intra-laboratory variation in the measurement of lipid peroxidation. Human plasma samples were exposed to UVA irradiation at different doses (0, 15 J, 20 J), encoded and shipped to 15 laboratories, where analyses of malondialdehyde, 4-hydroxynonenal and isoprostanes were conducted. The results demonstrate a low within-day-variation and a good correlation of results observed on two different days. However, high coefficients of variation were observed between the laboratories. Malondialdehyde determined by HPLC was found to be the most sensitive and reproducible lipid peroxidation product in plasma upon UVA treatment. It is concluded that measurement of malondialdehyde by HPLC has good analytical validity for inter-laboratory studies on lipid peroxidation in human EDTA-plasma samples, although it is acknowledged that this may not translate to biological validity.
Resumo:
In previous statnotes, the application of correlation and regression methods to the analysis of two variables (X,Y) was described. The most important statistic used to measure the degree of correlation between two variables is Pearson’s ‘product moment correlation coefficient’ (‘r’). The correlation between two variables may be due to their common relation to other variables. Hence, investigators using correlation studies need to be alert to the possibilities of spurious correlation and the methods of ‘partial correlation’ are one method of taking this into account. This statnote applies the methods of partial correlation to three scenarios. First, to a fairly obvious example of a spurious correlation resulting from the ‘size effect’ involving the relationship between the number of general practitioners (GP) and the number of deaths of patients in a town. Second, to the relationship between the abundance of the nitrogen-fixing bacterium Azotobacter in soil and three soil variables, and finally, to a more complex scenario, first introduced in Statnote 24involving the relationship between the growth of lichens in the field and climate.