Monitoring the covariance matrix with the VMAX chart

In this article, we propose a new statistic to control the covariance matrix of bivariate processes. This new statistic is based on the sample vat-lances of the two quality characteristics, shortly VMAX statistic. The points plotted on the chart correspond to the maximum of the values of these two variances. The reasons to consider the VMAX statistic instead of the generalized variance vertical bar S vertical bar are faster detection of process changes and better diagnostic feature, that is, with the VMAX statistic It is easier to identify the out-of-control variable.

A single statistic for monitoring the covariance matrix of bivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A Single Statistic for Monitoring the Covariance Matrix of Bivariate Processes

In this article, we present a new control chart for monitoring the covariance matrix in a bivariate process. In this method, n observations of the two variables were considered as if they came from a single variable (as a sample of 2n observations), and a sample variance was calculated. This statistic was used to build a new control chart specifically as a VMIX chart. The performance of the new control chart was compared with its main competitors: the generalized sampled variance chart, the likelihood ratio test, Nagao's test, probability integral transformation (v(t)), and the recently proposed VMAX chart. Among these statistics, only the VMAX chart was competitive with the VMIX chart. For shifts in both variances, the VMIX chart outperformed VMAX; however, VMAX showed better performance for large shifts (higher than 10%) in one variance.

An adaptive chart for monitoring the process mean and variance

Traditionally, an (X) over bar chart is used to control the process mean and an R chart is used to control the process variance. However, these charts are not sensitive to small changes in the process parameters. The adaptive ($) over bar and R charts might be considered if the aim is to detect small disturbances. Due to the statistical character of the joint (X) over bar and R charts with fixed or adaptive parameters, they are not reliable in identifing the nature of the disturbance, whether it is one that shifts the process mean, increases the process variance, or leads to a combination of both effects. In practice, the speed with which the control charts detect process changes may be more important than their ability in identifying the nature of the change. Under these circumstances, it seems to be advantageous to consider a single chart, based on only one statistic, to simultaneously monitor the process mean and variance. In this paper, we propose the adaptive non-central chi-square statistic chart. This new chart is more effective than the adaptive (X) over bar and R charts in detecting disturbances that shift the process mean, increase the process variance, or lead to a combination of both effects. Copyright (c) 2006 John Wiley & Sons, Ltd.

Synthetic control chart for monitoring the pprocess mean and variance

In this article, we consider the synthetic control chart with two-stage sampling (SyTS chart) to control the process mean and variance. During the first stage, one item of the sample is inspected; if its value X, is close to the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and the statistic T = Sigma [x(i) - mu(0) + xi sigma(0)](2) is computed taking into account all items of the sample. The design parameter is function of X-1. When the statistic T is larger than a specified value, the sample is classified as nonconforming. According to the synthetic procedure, the signal is based on Conforming Run Length (CRL). The CRL is the number of samples taken from the process since the previous nonconforming sample until the occurrence of the next nonconforming sample. If the CRL is sufficiently small, then a signal is generated. A comparative study shows that the SyTS chart and the joint X and S charts with double sampling are very similar in performance. However, from the practical viewpoint, the SyTS chart is more convenient to administer than the joint charts.

Monitoring the process mean and variance using a synthetic control chart with two-stage testing

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A synthetic control chart for monitoring the process mean and variance

Purpose - The aim of this paper is to present a synthetic chart based on the non-central chi-square statistic that is operationally simpler and more effective than the joint X̄ and R chart in detecting assignable cause(s). This chart will assist in identifying which (mean or variance) changed due to the occurrence of the assignable causes. Design/methodology/approach - The approach used is based on the non-central chi-square statistic and the steady-state average run length (ARL) of the developed chart is evaluated using a Markov chain model. Findings - The proposed chart always detects process disturbances faster than the joint X̄ and R charts. The developed chart can monitor the process instead of looking at two charts separately. Originality/value - The most important advantage of using the proposed chart is that practitioners can monitor the process by looking at only one chart instead of looking at two charts separately. © Emerald Group Publishing Limted.

Household-based malaria control in a highly endemic area of Africa (Tanzania): determinants of transmission and disease and indicators for monitoring - Kilombero Malaria Project

The Kilombero Malaria Project (KMP) attemps to define opperationally useful indicators of levels of transmission and disease and health system relevant monitoring indicators to evaluate the impact of disease control at the community or health facility level. The KMP is longitudinal community based study (N = 1024) in rural Southern Tanzania, investigating risk factors for malarial morbidity and developing household based malaria control strategies. Biweekly morbidity and bimonthly serological, parasitological and drug consumption surveys are carried out in all study households. Mosquito densities are measured biweekly in 50 sentinel houses by timed light traps. Determinants of transmission and indicators of exposure were not strongly aggregated within households. Subjective morbidity (recalled fever), objective morbidity (elevated body temperature and high parasitaemia) and chloroquine consumption were strongly aggregated within a few households. Nested analysis of anti-NANP40 antibody suggest that only approximately 30% of the titer variance can explained by household clustering and that the largest proportion of antibody titer variability must be explained by non-measured behavioral determinants relating to an individual's level of exposure within a household. Indicators for evaluation and monitoring and outcome measures are described within the context of health service management to describe control measure output in terms of community effectiveness.

Psychopathy and self-monitoring : additive and interactive effects on self-presentation tactics /

The purpose of this study was to determine the relative contributions of psychopathy and self-monitoring to the prediction of self-presentation tactics (behaviours that individuals use to manipulate their self-image). Psychopathy is composed of two main factors: Factor 1, which includes manipulativeness and shallow affect, and Factor 2, which includes irresponsibility and anti-social behaviours. Self-monitoring is a personality trait that distinguishes between those who adapt their behaviour to fit different social situations (high self-monitors) and those who behave as they feel regardless of social expectations (low selfmonitors). It was hypothesized that self-monitoring would moderate the relationship between psychopathy and self-presentation tactics. One hundred and forty-nine university students completed the Self-Monitoring Scale (Snyder, 1974), the Self-Report Psychopathy Scale - Version III (Paulhus et aI., in press), the Self-Presentation Tactics scale (Lee, S., et aI., 1999), the HEXACO-PI (a measure ofthe six major factors of personality; Lee, K., & Ashton, 2004), and six scenarios that were created as a supplementary measure of the selfpresentation tactics. Results of the hierarchical multiple regression analyses showed that self-monitoring did moderate the relationship between psychopathy and three of the selfpresentation tactics: apologies, disclaimers, and exemplification. Further, significant interactions were observed between Factor 1 and self-monitoring on apologies and the defensive tactics subscale, between Factor 2 and self-monitoring on self-handicapping, and between Factor 1 and Factor 2 on exemplification. Contrary to expectations, the main effect of self-monitoring was significant for the prediction of nine tactics, while psychopathy was significant for the prediction of seven tactics. This indicates that the role of these two personality traits in the explanation of self-presentation tactics tends to be additive in nature rather than interactive. In addition. Factor 2 alone did not account for a significant amount of variance in any of the tactics, while Factor 1 significantly predicted nine tactics. Results are discussed with regard to implications and possible directions for future research.

The effectiveness of a health versus appearance message on pregnant women's intentions to exercise postpartum : the moderating role of self-monitoring

Despite the confimied health benefits of exercise during the postpartum period, many new mothers are not sufficiently active. The present research aimed to examine the effectiveness of 2 types of messages on intention to exercise after giving birth on 2 groups of pregnant women (low and high self-monitors) using the Theory of Planned Behavior as a theoretical basis. Participants were 2 1 8 pregnant women 1 8 years of age and older (Mean age = 27.9 years, SD = 5.47), and in their second or third trimester. Women completed a demographics questionnaire, a self-monitoring (SM) scale and the Godin Leisure Time Exercise Questionnaire for current and pre-pregnancy exercise levels. They then read one of two brochures, describing either the health or appearance benefits of exercise for postpartum women. Women's attitudes, social norms, perceived behavioral control, and intentions to exercise postpartum were then assessed to determine whether one type of message (health or appearance) was more effective for each group. A MANOVA found no significant effect (p>0.05) for message type, SM, or their interaction. Possible reasons include the fact that the two messages may have been too similar, reading any message about exercise may result in intentions to exercise, or lack of attention given to the brochure. Given the lack of research in this area, more studies are necessary to confirm the present results. Two additional exploratory analyses were conducted. Pearson correlations found higher levels of pre-pregnancy exercise and current exercise to be associated with more positive attitudes, more positive subjective norms, higher perceived behavioral control, and higher intention to exercise postpartum. A hierarchical regression was conducted to determine the predictive utility of attitudes, subjective norms, and perceived behavioral control on intention for each self-monitoring group. Results of the analysis demonstrated the three independent variables significantly predicted intention (p < .001) in both groups, accounting for 58-62% of the variance in intention. For low self-monitors, attitude was the strongest predictor of intention, followed by perceived behavioral control and subjective norm. For high self-monitors, perceived behavioral control was the strongest predictors, followed by attitudes and subjective norm. The present study has practical and real world implications by contributing to our understanding of what types of messages, in a brochure format, are most effective in changing pregnant women's attitudes, subjective norm, perceived behavioral control and intention to exercise postpartum and provides ftirther support for the use of the Theory of Planned Behavior with this population.

A social-cognitive model of monitoring and its relationship to behaviour in a naturalistic observation : development and individual differences

years 8 months) and 24 older (M == 7 years 4 months) children. A Monitoring Process Model (MPM) was developed and tested in order to ascertain at which component process ofthe MPM age differences would emerge. The MPM had four components: (1) assessment; (2) evaluation; (3) planning; and (4) behavioural control. The MPM was assessed directly using a referential communication task in which the children were asked to make a series of five Lego buildings (a baseline condition and one building for each MPM component). Children listened to instructions from one experimenter while a second experimenter in the room (a confederate) intetjected varying levels ofverbal feedback in order to assist the children and control the component ofthe MPM. This design allowed us to determine at which "stage" ofprocessing children would most likely have difficulty monitoring themselves in this social-cognitive task. Developmental differences were obselVed for the evaluation, planning and behavioural control components suggesting that older children were able to be more successful with the more explicit metacomponents. Interestingly, however, there was no age difference in terms ofLego task success in the baseline condition suggesting that without the intelVention ofthe confederate younger children monitored the task about as well as older children. This pattern ofresults indicates that the younger children were disrupted by the feedback rather than helped. On the other hand, the older children were able to incorporate the feedback offered by the confederate into a plan ofaction. Another aim ofthis study was to assess similar processing components to those investigated by the MPM Lego task in a more naturalistic observation. Together the use ofthe Lego Task ( a social cognitive task) and the naturalistic social interaction allowed for the appraisal of cross-domain continuities and discontinuities in monitoring behaviours. In this vein, analyses were undertaken in order to ascertain whether or not successful performance in the MPM Lego Task would predict cross-domain competence in the more naturalistic social interchange. Indeed, success in the two latter components ofthe MPM (planning and behavioural control) was related to overall competence in the naturalistic task. However, this cross-domain prediction was not evident for all levels ofthe naturalistic interchange suggesting that the nature ofthe feedback a child receives is an important determinant ofresponse competency. Individual difference measures reflecting the children's general cognitive capacity (Working Memory and Digit Span) and verbal ability (vocabulary) were also taken in an effort to account for more variance in the prediction oftask success. However, these individual difference measures did not serve to enhance the prediction oftask performance in either the Lego Task or the naturalistic task. Similarly, parental responses to questionnaires pertaining to their child's temperament and social experience also failed to increase prediction oftask performance. On-line measures ofthe children's engagement, positive affect and anxiety also failed to predict competence ratings.

Uptake pathways: the potential of Bayesian belief networks to assist the management, monitoring and evaluation of development-orientated research

The effectiveness of development assistance has come under renewed scrutiny in recent years. In an era of growing economic liberalisation, research organisations are increasingly being asked to account for the use of public funds by demonstrating achievements. However, in the natural resources (NR) research field, conventional economic assessment techniques have focused on quantifying the impact achieved rather understanding the process that delivered it. As a result, they provide limited guidance for planners and researchers charged with selecting and implementing future research. In response, “pathways” or logic models have attracted increased interest in recent years as a remedy to this shortcoming. However, as commonly applied these suffer from two key limitations in their ability to incorporate risk and assess variance from plan. The paper reports the results of a case study that used a Bayesian belief network approach to address these limitations and outlines its potential value as a tool to assist the planning, monitoring and evaluation of development-orientated research.

Monitoring vegetation on railway embankments : supporting maintenance decisions

The national railway administrations in Scandinavia, Germany, and Austria mainly resort to manual inspections to control vegetation growth along railway embankments. Manually inspecting railways is slow and time consuming. A more worrying aspect concerns the fact that human observers are often unable to estimate the true cover of vegetation on railway embankments. Further human observers often tend to disagree with each other when more than one observer is engaged for inspection. Lack of proper techniques to identify the true cover of vegetation even result in the excess usage of herbicides; seriously harming the environment and threating the ecology. Hence work in this study has investigated aspects relevant to human variationand agreement to be able to report better inspection routines. This was studied by mainly carrying out two separate yet relevant investigations.First, thirteen observers were separately asked to estimate the vegetation cover in nine imagesacquired (in nadir view) over the railway tracks. All such estimates were compared relatively and an analysis of variance resulted in a significant difference on the observers’ cover estimates (p<0.05). Bearing in difference between the observers, a second follow-up field-study on the railway tracks was initiated and properly investigated. Two railway segments (strata) representingdifferent levels of vegetationwere carefully selected. Five sample plots (each covering an area of one-by-one meter) were randomizedfrom each stratumalong the rails from the aforementioned segments and ten images were acquired in nadir view. Further three observers (with knowledge in the railway maintenance domain) were separately asked to estimate the plant cover by visually examining theplots. Again an analysis of variance resulted in a significant difference on the observers’ cover estimates (p<0.05) confirming the result from the first investigation.The differences in observations are compared against a computer vision algorithm which detects the "true" cover of vegetation in a given image. The true cover is defined as the amount of greenish pixels in each image as detected by the computer vision algorithm. Results achieved through comparison strongly indicate that inconsistency is prevalent among the estimates reported by the observers. Hence, an automated approach reporting the use of computer vision is suggested, thus transferring the manual inspections into objective monitored inspections

A control chart based on sample ranges for monitoring the covariance matrix of the multivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A new chart based on sample variances for monitoring the covariance matrix of multivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)