Data analysis /

"In any comprehensive research project, there are essentially five steps. First, one starts with a literature review with regard to a particular research question. Second, one seeks to develop a theory. Third, the research question is finalized, frequently in the form of a hypothesis to be tested. Fourth, data are collected. Fifth, the subject matter of this paper, the data are analyzed in order to come to a resolution of the research question. There are two general approaches to analyzing research data. If the data were gathered concerning a 'research question,' a description of the data may be sufficient. However, if the data were gathered to accept or reject a formal hypothesis, statistical analysis is usually in order. This paper briefly surveys the principal data analysis methodologies that are available."

Demographic and Geographic Heterogeneity between Subgroups of Cyclists

Thesis (Master's)--University of Washington, 2016-06

Using multivariate analysis to predict the behaviour of soils under effluent irrigation

Onsite wastewater treatment systems aim to assimilate domestic effluent into the environment. Unfortunately failure of such systems is common and inadequate effluent treatment can have serious environmental implications. The capacity of a particular soil to treat wastewater will change over time. The physical properties influence the rate of effluent movement through the soil and its chemical properties dictate the ability to renovate effluent. A research project was undertaken to determine the role that physical and chemical soil properties play in predicting the long-term behaviour of soil under effluent irrigation and to determine if they have a potential function as early indicators of adverse effects of effluent irrigation on treatment sustainability. Principal Component Analysis (PCA) and Cluster Analysis grouped the soils independently of their soil classifications and allowed us to distinguish the most suitable soils for sustainable long term effluent irrigation and determine the most influential soil parameters to characterise them. Multivariate analysis allowed a clear distinction between soils based on the cation exchange capacities. This in turn correlated well with the soil mineralogy. Mixed mineralogy soils in particular sodium or magnesium dominant soils are the most susceptible to dispersion under effluent irrigation. The soil Exchangeable Sodium Percentage (ESP) was identified as a crucial parameter and was highly correlated with percentage clay, electrical conductivity, exchangeable sodium, exchangeable magnesium and low Ca:Mg ratios (less than 0.5).

Validation of the Quality of Life Inventory for patients with anxiety and depression

Background: In 1992, Frisch et al (Psychol Assess. 1992;4:92- 10 1) developed the Quality of Life Inventory (QOLI) to measure the concept of quality of life (QOL) because it has long been thought to be related to both physical and emotional well-being. However, the psychometric properties of the QOLI in clinical populations are still in debate. The present study examined the factor structure of QOLI and reported its validity and reliability in a clinical sample. Method: Two hundred seventeen patients with anxiety and depressive disorders completed the QOLI and additional questionnaires measuring symptoms (Zung Self-rating Depression Scale, Beck Anxiety Inventory, Fear Questionnaire, Depression Anxiety Stress Scale-Stress) and subjective well-being (Satisfaction With Life Scale) were also used. Results: Exploratory factor analysis via the principal components method, with oblique rotation, revealed a 2-factor structure that accounted for 42.73% of the total variance, and a subsequent confirmatory factor analysis suggested a moderate fit of the data to this model. The 2 factors appeared to describe self-oriented QOL and externally oriented QOL. The Cronbach alpha coefficients were 0.85 for the overall QOLI score, 0.81 for the first factor, and 0.75 for the second factor. Conclusion: Consistent evidence was also found to support the concurrent, discriminant, predictive, and criterion-related validity of the QOLI. (c) 2006 Elsevier Inc. All rights reserved.

Mixtures of probabilistic principal component analysers

Principal component analysis (PCA) is one of the most popular techniques for processing, compressing and visualising data, although its effectiveness is limited by its global linearity. While nonlinear variants of PCA have been proposed, an alternative paradigm is to capture data complexity by a combination of local linear PCA projections. However, conventional PCA does not correspond to a probability density, and so there is no unique way to combine PCA models. Previous attempts to formulate mixture models for PCA have therefore to some extent been ad hoc. In this paper, PCA is formulated within a maximum-likelihood framework, based on a specific form of Gaussian latent variable model. This leads to a well-defined mixture model for probabilistic principal component analysers, whose parameters can be determined using an EM algorithm. We discuss the advantages of this model in the context of clustering, density modelling and local dimensionality reduction, and we demonstrate its application to image compression and handwritten digit recognition.

The West Midlands road transport industry

The object of this project was to identify those elements of management practice which characterised firms in the West Midlands Road Transport Industry. The object being to establish the contents of what might be termed a management policy portfolio for growth. The First Phase was the review of those factors which were generally accepted as having an influence on the success rate of transport firms in order to ascertain if they explained observed patterns. Secondly, if this were not the case, to instigate a field work study to isolate those policies which were associated with growth organizations. Investigation of the vehicle movements for the entire West Midlands Fleet over a complete licence cycle suggested that conventional explanations could not fully account for the observed patterns. To carry out the second phase of the study a sample of growth firms were visited in order to measure their attitudes on a range of factors hypothesised to affect growth. Field data were analysed to establish management activities over a wide range of areas and the results further investigated through a Principal Components and Cluster Analysis programme. The outcome of the study indicates that some past attitudes on the skills and attitudes of transport managers may have to be re-examined. As a result, the project produced a new classification of road transport firms based not on the conventional categories of long and short haul, or the types of traffics carried, but on the marketing policies and management skills employed within the organization.

The use of spot simulation imagery for forestry mapping and management

SPOT simulation imagery was acquired for a test site in the Forest of Dean in Gloucestershire, U.K. This data was qualitatively and quantitatively evaluated for its potential application in forest resource mapping and management. A variety of techniques are described for enhancing the image with the aim of providing species level discrimination within the forest. Visual interpretation of the imagery was more successful than automated classification. The heterogeneity within the forest classes, and in particular between the forest and urban class, resulted in poor discrimination using traditional `per-pixel' automated methods of classification. Different means of assessing classification accuracy are proposed. Two techniques for measuring textural variation were investigated in an attempt to improve classification accuracy. The first of these, a sequential segmentation method, was found to be beneficial. The second, a parallel segmentation method, resulted in little improvement though this may be related to a combination of resolution in size of the texture extraction area. The effect on classification accuracy of combining the SPOT simulation imagery with other data types is investigated. A grid cell encoding technique was selected as most appropriate for storing digitised topographic (elevation, slope) and ground truth data. Topographic data were shown to improve species-level classification, though with sixteen classes overall accuracies were consistently below 50%. Neither sub-division into age groups or the incorporation of principal components and a band ratio significantly improved classification accuracy. It is concluded that SPOT imagery will not permit species level classification within forested areas as diverse as the Forest of Dean. The imagery will be most useful as part of a multi-stage sampling scheme. The use of texture analysis is highly recommended for extracting maximum information content from the data. Incorporation of the imagery into a GIS will both aid discrimination and provide a useful management tool.

Dynamic ocular thermography

The ability to measure ocular surface temperature (OST) with thermal imaging offers potential insight into ocular physiology that has been acknowledged in the literature. The TH7102MX thermo-camera (NEC San-ei, Japan) continuously records dynamic information about OST without sacrificing spatial resolution. Using purpose-designed image analysis software, it was possible to select and quantify the principal components of absolute temperature values and the magnitude plus rate of temperature change that followed blinking. The techniques was examined for repeatability, reproducibility and the effects of extrinsic factors: a suitable experimental protocol was thus developed. The precise source of the measured thermal radiation has previously been subject toe dispute: in this thesis, the results of a study examining the relationships between physical parameters of the anterior eye and OST, confirmed a principal role for the tear film in OST. The dynamic changes in OST were studied in a large group of young subjects: quantifying the post-blink changes in temperature with time also established a role for tear flow dynamics in OST. Using dynamic thermography, the effects of hydrogel contact lens wear on OST were investigated: a model eye for in vivo work, and both neophyte and adapted contact lens wearers for in vivo studies. Significantly greater OST was observed in contact lens wearers, particularly with silicone hydrogel lenses compared to etafilcon A, and tended to be greatest when lenses had been worn continuously. This finding is important to understanding the ocular response to contact lens wear. In a group of normal subjects, dynamic thermography appeared to measure the ocular response to the application of artificial tear drops: this may prove to be a significant research and clinical tool.

The classification of HLA supertypes by GRID/CPCA and hierarchical clustering methods

Biological experiments often produce enormous amount of data, which are usually analyzed by data clustering. Cluster analysis refers to statistical methods that are used to assign data with similar properties into several smaller, more meaningful groups. Two commonly used clustering techniques are introduced in the following section: principal component analysis (PCA) and hierarchical clustering. PCA calculates the variance between variables and groups them into a few uncorrelated groups or principal components (PCs) that are orthogonal to each other. Hierarchical clustering is carried out by separating data into many clusters and merging similar clusters together. Here, we use an example of human leukocyte antigen (HLA) supertype classification to demonstrate the usage of the two methods. Two programs, Generating Optimal Linear Partial Least Square Estimations (GOLPE) and Sybyl, are used for PCA and hierarchical clustering, respectively. However, the reader should bear in mind that the methods have been incorporated into other software as well, such as SIMCA, statistiXL, and R.

Development of a new student evaluation instrument of instructor effectiveness in online courses

The purpose of this study was to (a) develop an evaluation instrument capable of rating students' perceptions of the instructional quality of an online course and the instructor’s performance, and (b) validate the proposed instrument with a study conducted at a major public university. The instrument was based upon the Seven Principles of Good Practice for Undergraduate Education (Chickering & Gamson, 1987). The study examined four specific questions. 1. Is the underlying factor structure of the new instrument consistent with Chickering and Gamson's Seven Principles? 2. Is the factor structure of the new instrument invariant for male and female students? 3. Are the scores on the new instrument related students’ expected grades? 4. Are the scores on the new instrument related to the students' perceived course workload? ^ The instrument was designed to measure students’ levels of satisfaction with their instruction, and also gathered information concerning the students’ sex, the expected grade in the course, and the students’ perceptions of the amount of work required by the course. A cluster sample consisting of an array of online courses across the disciplines yielded a total 297 students who responded to the online survey. The students for each course selected were asked to rate their instructors with the newly developed instrument. ^ Question 1 was answered using exploratory factor analysis, and yielded a factor structure similar to the Seven Principles.^ Question 2 was answered by separately factor-analyzing the responses of male and female students and comparing the factor structures. The resulting factor structures for men and women were different. However, 14 items could be realigned under five factors that paralleled some of the Seven Principles. When the scores of only those 14 items were entered in two principal components factor analyses using only men and only women, respectively and restricting the factor structure to five factors, the factor structures were the same for men and women.^ A weak positive relationship between students’ expected grades and their scores on the instrument was found (Question 3). There was no relationship between students’ perceived workloads for the course and their scores on the instrument (Question 4).^

Stream dissolved organic matter bioavailability and composition in watersheds underlain with discontinuous permafrost

We examined the impact of permafrost on dissolved organic matter (DOM) composition in Caribou-Poker Creeks Research Watershed (CPCRW), a watershed underlain with discontinuous permafrost, in interior Alaska. We analyzed long term data from watersheds underlain with varying degrees of permafrost, sampled springs and thermokarsts, used fluorescence spectroscopy, and measured the bioavailabity of dissolved organic carbon (DOC). Permafrost driven patterns in hydrology and vegetation influenced DOM patterns in streams, with the stream draining the high permafrost watershed having higher DOC and dissolved organic nitrogen (DON) concentrations, higher DOC:- DON and greater specific ultraviolet absorbance (SUVA) than the streams draining the low and medium permafrost watersheds. Streams, springs and thermokarsts exhibited a wide range of DOC and DON concentrations (1.5–37.5 mgC/L and 0.14–1.26 mgN/L, respectively), DOC:DON (7.1–42.8) and SUVA (1.5–4.7 L mgC-1 m-1). All sites had a high proportion of humic components, a low proportion of protein components, and a low fluorescence index value (1.3–1.4), generally consistent with terrestrially derivedDOM. Principal component analysis revealed distinct groups in our fluorescence data determined by diagenetic processing and DOM source. The proportion of bioavailable DOC ranged from 2 to 35%, with the proportion of tyrosine- and tryptophan-like fluorophores in the DOM being a major predictor of DOC loss (p\0.05, R2 = 0.99). Our results indicate that the degradation of permafrost in CPCRW will result in a decrease in DOC and DON concentrations, a decline in DOC:DON, and a reduction in SUVA, possibly accompanied by

Comparative study of dissolved organic matter from groundwater and surface water in the Florida coastal Everglades using multi-dimensional spectrofluorometry combined with multivariate statistics

Dissolved organic matter (DOM) in groundwater and surface water samples from the Florida coastal Everglades were studied using excitation–emission matrix fluorescence modeled through parallel factor analysis (EEM-PARAFAC). DOM in both surface and groundwater from the eastern Everglades S332 basin reflected a terrestrial-derived fingerprint through dominantly higher abundances of humic-like PARAFAC components. In contrast, surface water DOM from northeastern Florida Bay featured a microbial-derived DOM signature based on the higher abundance of microbial humic-like and protein-like components consistent with its marine source. Surprisingly, groundwater DOM from northeastern Florida Bay reflected a terrestrial-derived source except for samples from central Florida Bay well, which mirrored a combination of terrestrial and marine end-member origin. Furthermore, surface water and groundwater displayed effects of different degradation pathways such as photodegradation and biodegradation as exemplified by two PARAFAC components seemingly indicative of such degradation processes. Finally, Principal Component Analysis of the EEM-PARAFAC data was able to distinguish and classify most of the samples according to DOM origins and degradation processes experienced, except for a small overlap of S332 surface water and groundwater, implying rather active surface-to-ground water interaction in some sites particularly during the rainy season. This study highlights that EEM-PARAFAC could be used successfully to trace and differentiate DOM from diverse sources across both horizontal and vertical flow profiles, and as such could be a convenient and useful tool for the better understanding of hydrological interactions and carbon biogeochemical cycling.

Solar radiation–enhanced dissolution of particulate organic matter from coastal marine sediments

We investigated the influence of solar radiation on the transfer of organic matter from the particulate to dissolved phase during resuspension of coastal sediments collected from seven sites across Florida Bay (organic carbon values ranged from 2% to 9% by weight). Sediments were resuspended in oligotrophic seawater for 48 h in 1-liter quartz flasks in the dark and under simulated solar radiation (SunTest XLS+) at wet weight concentrations of 100 mg L21 and 1 g L21 (dry weights ranged from 27 to 630 mg L21). There were little to no dissolved organic carbon (DOC) increases in dark resuspensions, but substantial DOC increases occurred in irradiated resuspensions. DOC levels increased 4 mg C L21 in an irradiated 1 g L21 suspension (dry weight 400 mg L21) of an organic-rich (7% organic carbon) sediment. At a particle load commonly found in coastal waters (dry weight 40 mg L21), an irradiated suspension of the same organic-rich sediment produced 1 mg C L21. DOC increases in irradiated resuspensions were well-correlated with particulate organic carbon (POC) added. Photodissolution of POC ranged from 6% to 15% at high sediment levels and 10% to 33% at low sediment levels. Parallel factor analysis modeling of excitation-emission matrix fluorescence data (EEM PARAFAC) suggested the dissolved organic matter (DOM) produced during photodissolution included primarily humic-like components and a less important input of protein-like components. Principal component analysis (PCA) of EEM data revealed a marked similarity in the humic character of photodissolved DOM from organic-rich sediments and the humic character of Florida Bay waters.

Occupational therapists' attitudes toward family -centered care

The purpose of this study was to examine pediatric occupational therapists attitudes towards family-centered care. Specific attributes identified by the literature (professional characteristics, educational experiences and organizational culture) were investigated to determine their influence on these attitudes. Study participants were 250 pediatric occupational therapists who were randomly selected from the American Occupational Therapy Association special interest sections. ^ Participants received a mail packet with three instruments to complete and mail back within 2 weeks. The instruments were (a) the Professional Attitude Scale, (b) the Professional Characteristics Questionnaire, and (c) the Family-Centered Program Rating Scale. There was a 50% return rate. Data analysis was conducted in SPSS using descriptive statistics, correlations and regression analysis. ^ The analysis showed that pediatric occupational therapists working in various practice settings demonstrate favorable attitudes toward family-centered care as measured by the Professional Attitude Scale. There was no correlation between professional characteristics and educational experiences to therapists' attitudes. A moderate correlation (r = .368, p < .05) was found between the occupational therapists attitudes and the organizational culture of their workplaces. A factor analysis was conducted on the organizational culture instrument (FamPRS) as this sample was exclusively pediatric occupational therapists and the original sample was interdisciplinary professionals. Two factors were extracted using a principal components extraction and varimax rotation, in addition to examination of the scree plot. These two factors accounted for 50% of the total variance of the scores on the instrument. Factor 1, called empowerment accounted for 45.6% of the variance, and Factor 2, responsiveness accounted for 4.3% of the variance of the entire instrument. Stepwise regression analysis demonstrated that these two factors accounted for 16% of the variance toward attitudes clinicians hold toward family-centered care. These factors support the tenets of family-centered care; empowering parents to be leaders in their child's health care and helping organizations become more responsive to family needs. ^ These study findings suggest that organizational culture has some influence on occupational therapists attitudes toward family-centered care (R 2 = .16). These findings suggest educators should consider families as valuable resources when considering program planning in family-centered care at preservice and workplace settings. ^

Evaluating the Distribution of Terrestrial Dissolved Organic Matter in a Complex Coastal Ecosystem Using Fluorescence Spectroscopy

The coastal zone of the Florida Keys features the only living coral reef in the continental United States and as such represents a unique regional environmental resource. Anthropogenic pressures combined with climate disturbances such as hurricanes can affect the biogeochemistry of the region and threaten the health of this unique ecosystem. As such, water quality monitoring has historically been implemented in the Florida Keys, and six spatially distinct zones have been identified. In these studies however, dissolved organic matter (DOM) has only been studied as a quantitative parameter, and DOM composition can be a valuable biogeochemical parameter in assessing environmental change in coastal regions. Here we report the first data of its kind on the application of optical properties of DOM, in particular excitation emission matrix fluorescence with parallel factor analysis (EEM-PARAFAC), throughout these six Florida Keys regions in an attempt to assess spatial differences in DOM sources. Our data suggests that while DOM in the Florida Keys can be influenced by distant terrestrial environments such as the Everglades, spatial differences in DOM distribution were also controlled in part by local surface runoff/fringe mangroves, contributions from seasgrass communities, as well as the reefs and waters from the Florida Current. Application of principal component analysis (PCA) of the relative abundance of EEM-PARAFAC components allowed for a clear distinction between the sources of DOM (allochthonous vs. autochthonous), between different autochthonous sources and/or the diagenetic status of DOM, and further clarified contribution of terrestrial DOM in zones where levels of DOM were low in abundance. The combination between EEM-PARAFAC and PCA proved to be ideally suited to discern DOM composition and source differences in coastal zones with complex hydrology and multiple DOM sources.