Data analysis methods in optometry Part 8: Principal components analysis (PCA) and factor analysis (FA)

PCA/FA is a method of analyzing complex data sets in which there are no clearly defined X or Y variables. It has multiple uses including the study of the pattern of variation between individual entities such as patients with particular disorders and the detailed study of descriptive variables. In most applications, variables are related to a smaller number of ‘factors’ or PCs that account for the maximum variance in the data and hence, may explain important trends among the variables. An increasingly important application of the method is in the ‘validation’ of questionnaires that attempt to relate subjective aspects of a patients experience with more objective measures of vision.

The application of methods of uncertain reasoning to the biological classification of river water quality

This thesis presents an investigation into the application of methods of uncertain reasoning to the biological classification of river water quality. Existing biological methods for reporting river water quality are critically evaluated, and the adoption of a discrete biological classification scheme advocated. Reasoning methods for managing uncertainty are explained, in which the Bayesian and Dempster-Shafer calculi are cited as primary numerical schemes. Elicitation of qualitative knowledge on benthic invertebrates is described. The specificity of benthic response to changes in water quality leads to the adoption of a sensor model of data interpretation, in which a reference set of taxa provide probabilistic support for the biological classes. The significance of sensor states, including that of absence, is shown. Novel techniques of directly eliciting the required uncertainty measures are presented. Bayesian and Dempster-Shafer calculi were used to combine the evidence provided by the sensors. The performance of these automatic classifiers was compared with the expert's own discrete classification of sampled sites. Variations of sensor data weighting, combination order and belief representation were examined for their effect on classification performance. The behaviour of the calculi under evidential conflict and alternative combination rules was investigated. Small variations in evidential weight and the inclusion of evidence from sensors absent from a sample improved classification performance of Bayesian belief and support for singleton hypotheses. For simple support, inclusion of absent evidence decreased classification rate. The performance of Dempster-Shafer classification using consonant belief functions was comparable to Bayesian and singleton belief. Recommendations are made for further work in biological classification using uncertain reasoning methods, including the combination of multiple-expert opinion, the use of Bayesian networks, and the integration of classification software within a decision support system for water quality assessment.

Objective methods for anterior ocular grading

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.

Statnote 24: Multiple regression

In previous statnotes, the application of correlation and regression methods to the analysis of two variables (X,Y) was described. These methods can be used to determine whether there is a linear relationship between the two variables, whether the relationship is positive or negative, to test the degree of significance of the linear relationship, and to obtain an equation relating Y to X. This Statnote extends the methods of linear correlation and regression to situations where there are two or more X variables, i.e., 'multiple linear regression’.

Multiple frequency functional connectivity in the hand somatosensory network:an EEG study

Objective: To investigate the dynamics of communication within the primary somatosensory neuronal network. Methods: Multichannel EEG responses evoked by median nerve stimulation were recorded from six healthy participants. We investigated the directional connectivity of the evoked responses by assessing the Partial Directed Coherence (PDC) among five neuronal nodes (brainstem, thalamus and three in the primary sensorimotor cortex), which had been identified by using the Functional Source Separation (FSS) algorithm. We analyzed directional connectivity separately in the low (1-200. Hz, LF) and high (450-750. Hz, HF) frequency ranges. Results: LF forward connectivity showed peaks at 16, 20, 30 and 50. ms post-stimulus. An estimate of the strength of connectivity was modulated by feedback involving cortical and subcortical nodes. In HF, forward connectivity showed peaks at 20, 30 and 50. ms, with no apparent feedback-related strength changes. Conclusions: In this first non-invasive study in humans, we documented directional connectivity across subcortical and cortical somatosensory pathway, discriminating transmission properties within LF and HF ranges. Significance: The combined use of FSS and PDC in a simple protocol such as median nerve stimulation sheds light on how high and low frequency components of the somatosensory evoked response are functionally interrelated in sustaining somatosensory perception in healthy individuals. Thus, these components may potentially be explored as biomarkers of pathological conditions. © 2012 International Federation of Clinical Neurophysiology.

Interactions between landcover pattern and geospatial processing methods:effects on landscape metrics and classification accuracy

Remote sensing data is routinely used in ecology to investigate the relationship between landscape pattern as characterised by land use and land cover maps, and ecological processes. Multiple factors related to the representation of geographic phenomenon have been shown to affect characterisation of landscape pattern resulting in spatial uncertainty. This study investigated the effect of the interaction between landscape spatial pattern and geospatial processing methods statistically; unlike most papers which consider the effect of each factor in isolation only. This is important since data used to calculate landscape metrics typically undergo a series of data abstraction processing tasks and are rarely performed in isolation. The geospatial processing methods tested were the aggregation method and the choice of pixel size used to aggregate data. These were compared to two components of landscape pattern, spatial heterogeneity and the proportion of landcover class area. The interactions and their effect on the final landcover map were described using landscape metrics to measure landscape pattern and classification accuracy (response variables). All landscape metrics and classification accuracy were shown to be affected by both landscape pattern and by processing methods. Large variability in the response of those variables and interactions between the explanatory variables were observed. However, even though interactions occurred, this only affected the magnitude of the difference in landscape metric values. Thus, provided that the same processing methods are used, landscapes should retain their ranking when their landscape metrics are compared. For example, highly fragmented landscapes will always have larger values for the landscape metric "number of patches" than less fragmented landscapes. But the magnitude of difference between the landscapes may change and therefore absolute values of landscape metrics may need to be interpreted with caution. The explanatory variables which had the largest effects were spatial heterogeneity and pixel size. These explanatory variables tended to result in large main effects and large interactions. The high variability in the response variables and the interaction of the explanatory variables indicate it would be difficult to make generalisations about the impact of processing on landscape pattern as only two processing methods were tested and it is likely that untested processing methods will potentially result in even greater spatial uncertainty. © 2013 Elsevier B.V.

Developing critical understanding in HRM students:using innovative teaching methods to encourage deep approaches to study

Purpose – This paper aims to focus on developing critical understanding in human resource management (HRM) students in Aston Business School, UK. The paper reveals that innovative teaching methods encourage deep approaches to study, an indicator of students reaching their own understanding of material and ideas. This improves student employability and satisfies employer need. Design/methodology/approach – Student response to two second year business modules, matched for high student approval rating, was collected through focus group discussion. One module was taught using EBL and the story method, whilst the other used traditional teaching methods. Transcripts were analysed and compared using the structure of the ASSIST measure. Findings – Critical understanding and transformative learning can be developed through the innovative teaching methods of enquiry-based learning (EBL) and the story method. Research limitations/implications – The limitation is that this is a single case study comparing and contrasting two business modules. The implication is that the study should be replicated and developed in different learning settings, so that there are multiple data sets to confirm the research finding. Practical implications – Future curriculum development, especially in terms of HE, still needs to encourage students and lecturers to understand more about the nature of knowledge and how to learn. The application of EBL and the story method is described in a module case study – “Strategy for Future Leaders”. Originality/value – This is a systematic and comparative study to improve understanding of how students and lecturers learn and of the context in which the learning takes place.

Catching transcriptional regulation by thermostatistical modeling

Gene expression is frequently regulated by multiple transcription factors (TFs). Thermostatistical methods allow for a quantitative description of interactions between TFs, RNA polymerase and DNA, and their impact on the transcription rates. We illustrate three different scales of the thermostatistical approach: the microscale of TF molecules, the mesoscale of promoter energy levels and the macroscale of transcriptionally active and inactive cells in a cell population. We demonstrate versatility of combinatorial transcriptional activation by exemplifying logic functions, such as AND and OR gates. We discuss a metric for cell-to-cell transcriptional activation variability known as Fermi entropy. Suitability of thermostatistical modeling is illustrated by describing the experimental data on transcriptional induction of NF?B and the c-Fos protein.

Knowledge elicitation and knowledge representation in a large domain with multiple experts

This paper describes the knowledge elicitation and knowledge representation aspects of a system being developed to help with the design and maintenance of relational data bases. The size algorithmic components. In addition, the domain contains multiple experts, but any given expert's knowledge of this large domain is only partial. The paper discusses the methods and techniques used for knowledge elicitation, which was based on a "broad and shallow" approach at first, moving to a "narrow and deep" one later, and describes the models used for knowledge representation, which were based on a layered "generic and variants" approach. © 1995.

Performance modelling and analysis of multiple coexisting IEEE 802.15.4 wireless sensor networks

With the features of low-power and flexible networking capabilities IEEE 802.15.4 has been widely regarded as one strong candidate of communication technologies for wireless sensor networks (WSNs). It is expected that with an increasing number of deployments of 802.15.4 based WSNs, multiple WSNs could coexist with full or partial overlap in residential or enterprise areas. As WSNs are usually deployed without coordination, the communication could meet significant degradation with the 802.15.4 channel access scheme, which has a large impact on system performance. In this thesis we are motivated to investigate the effectiveness of 802.15.4 networks supporting WSN applications with various environments, especially when hidden terminals are presented due to the uncoordinated coexistence problem. Both analytical models and system level simulators are developed to analyse the performance of the random access scheme specified by IEEE 802.15.4 medium access control (MAC) standard for several network scenarios. The first part of the thesis investigates the effectiveness of single 802.15.4 network supporting WSN applications. A Markov chain based analytic model is applied to model the MAC behaviour of IEEE 802.15.4 standard and a discrete event simulator is also developed to analyse the performance and verify the proposed analytical model. It is observed that 802.15.4 networks could sufficiently support most WSN applications with its various functionalities. After the investigation of single network, the uncoordinated coexistence problem of multiple 802.15.4 networks deployed with communication range fully or partially overlapped are investigated in the next part of the thesis. Both nonsleep and sleep modes are investigated with different channel conditions by analytic and simulation methods to obtain the comprehensive performance evaluation. It is found that the uncoordinated coexistence problem can significantly degrade the performance of 802.15.4 networks, which is unlikely to satisfy the QoS requirements for many WSN applications. The proposed analytic model is validated by simulations which could be used to obtain the optimal parameter setting before WSNs deployments to eliminate the interference risks.

Visual field severity indices demonstrate dose-dependent visual loss from Vigabatrin therapy

Purpose: The aims of this study were to develop an algorithm to accurately quantify Vigabatrin (VGB)-induced central visual field loss and to investigate the relationship between visual field loss and maximum daily dose, cumulative dose and duration of dose. Methods: The sample comprised 31 patients (mean age 37.9 years; SD 14.4 years) diagnosed with epilepsy and exposed to VGB. Each participant underwent standard automated static visual field examination of the central visual field. Central visual field loss was determined using continuous scales quantifying severity in terms of area and depth of defect and additionally by symmetry of defect between the two eyes. A simultaneous multiple regression model was used to explore the relationship between these visual field parameters and the drug predictor variables. Results: The regression model indicated that maximum VGB dose was the only factor to be significantly correlated with individual eye severity (right eye: p = 0.020; left eye: p = 0.012) and symmetry of visual field defect (p = 0.024). Conclusions: Maximum daily dose was the single most reliable indicator of those patients likely to exhibit visual field defects due to VGB. These findings suggest that high maximum dose is more likely to result in visual field defects than high cumulative doses or those of long duration.

Predicting class I major histocompatibility complex (MHC) binders using multivariate statistics:comparison of discriminant analysis and multiple linear regression

The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.

Development and psychometric evaluation of a new team effectiveness scale for all types of community adult mental health teams:a mixed-methods approach

Defining 'effectiveness' in the context of community mental health teams (CMHTs) has become increasingly difficult under the current pattern of provision required in National Health Service mental health services in England. The aim of this study was to establish the characteristics of multi-professional team working effectiveness in adult CMHTs to develop a new measure of CMHT effectiveness. The study was conducted between May and November 2010 and comprised two stages. Stage 1 used a formative evaluative approach based on the Productivity Measurement and Enhancement System to develop the scale with multiple stakeholder groups over a series of qualitative workshops held in various locations across England. Stage 2 analysed responses from a cross-sectional survey of 1500 members in 135 CMHTs from 11 Mental Health Trusts in England to determine the scale's psychometric properties. Based on an analysis of its structural validity and reliability, the resultant 20-item scale demonstrated good psychometric properties and captured one overall latent factor of CMHT effectiveness comprising seven dimensions: improved service user well-being, creative problem-solving, continuous care, inter-team working, respect between professionals, engagement with carers and therapeutic relationships with service users. The scale will be of significant value to CMHTs and healthcare commissioners both nationally and internationally for monitoring, evaluating and improving team functioning in practice.

Identifying frames:a comparison of research methods

Framing plays an important role in public policy. Interest groups strategically highlight some aspects of a policy proposal while downplaying others in order to steer the policy debate in a favorable direction. Despite the importance of framing, we still know relatively little about the framing strategies of interest groups due to methodological difficulties that have prevented scholars from systematically studying interest group framing across a large number of interest groups and multiple policy debates. This article therefore provides an overview of three novel research methods that allow researchers to systematically measure interest group frames. More specifically, this article introduces a word-based quantitative text analysis technique, a manual, computer-assisted content analysis approach and face-to-face interviews designed to systematically identify interest group frames. The results generated by all three techniques are compared on the basis of a case study of interest group framing in an environmental policy debate in the European Union.

Agitation conditions for the culture and detachment of hMSCs from microcarriers in multiple bioreactor platforms

In our recent work in different bioreactors up to 2.5L in scale, we have successfully cultured hMSCs using the minimum agitator speed required for complete microcarrier suspension, N JS. In addition, we also reported a scaleable protocol for the detachment from microcarriers in spinner flasks of hMSCs from two donors. The essence of the protocol is the use of a short period of intense agitation in the presence of enzymes such that the cells are detached; but once detachment is achieved, the cells are smaller than the Kolmogorov scale of turbulence and hence not damaged. Here, the same approach has been effective for culture at N JS and detachment in-situ in 15mL ambr™ bioreactors, 100mL spinner flasks and 250mL Dasgip bioreactors. In these experiments, cells from four different donors were used along with two types of microcarrier with and without surface coatings (two types), four different enzymes and three different growth media (with and without serum), a total of 22 different combinations. In all cases after detachment, the cells were shown to retain their desired quality attributes and were able to proliferate. This agitation strategy with respect to culture and harvest therefore offers a sound basis for a wide range of scales of operation.