A Simulation Study Of The Impact Of Forecast Recovery For Control Charts Applied To ARMA Processes

Forecast-based schemes are often used to monitor autocorrelated processes, but the resulting forecast recovery has a significant effect on the performance of control charts. This article describes forecast recovery for autocorrelated processes, and the resulting simulation study is used to explain the performance of control charts applied to forecast errors

Evaluation of three lack of fit tests in linear regression models

A key diagnostic in the analysis of linear regression models is whether the fitted model is appropriate for the observed data. The classical lack of fit test is used for testing the adequacy of a linear regression model when replicates are available. While many efforts have been made in finding alternative lack of fit tests for models without replicates, this paper focuses on studying the efficacy of three tests: the classical lack of fit test, Utts' (1982) test, Burn & Ryan's (1983) test. The powers of these tests are computed for a variety of situations. Comments and conclusions on the overall performance of these tests are made, including recommendations for future studies.

Multivariate Forecast Based Control Charting Schemes

Recently, much research had been performed in the area of control charting techniques for monitoring autocorrelated processes, especially regarding forecast based monitoring schemes. Forecast based monitoring schemes involve fitting an appropriate time-series model to the process, generating one step ahead forecast errors, and monitoring the forecast errors with traditional control charts. Another recent suggestion involved generating both the one-step-ahead and two-step-ahead forecast errors, then monitoring them with multivariate control charts. This article investigates the suggested multivariate approaches in regards to various ARMA(1,1) and AR(1) processes and shows the performance of the control charts relative to their univariate counterparts

Alarm rates for quality control charts

There is a direct relationship between a single alarm probability and the average run length only for basic Shewhart charts such as the . Alarm rates are defined in this paper that can be applied with charts such as the cumulative sum (CUSUM) chart and the exponentially weighted moving average (EWMA) chart that base decisions on several observations, not just the most recent one. Methods for determining EWMA chart limits are compared on the basis of their false alarm rates. It is shown how control charts can be more flexibly and carefully defined by considering a desired pattern of in-control false alarm rates in conjunction with a desired in-control average run length.Statistical process control Exponentially weighted moving average control chart Average run length

Association between stroke risk factors and access to care

A number of medically diagnosed risk factors are associated with an increased risk of having a stroke. Individuals recognized with hypertension, diabetes, and dyslipidemia all show greater probability of experiencing a stroke. Rural inhabitants are often considered to have limited access to health care, thus frequently decreasing the likelihood of their being aware of, treated, or controlled for these and other stroke-risk factors. This investigation provides an avenue for exploration into the association nontraditional risk factors for stroke, rural/urban designation, and travel time to a usual source of health care have on awareness, treatment, and control of hypertension, diabetes, and dyslipidemia. The association between awareness, treatment, and control of stroke-risk factors and an individual's rural/urban status was investigated to identify geographic disparities. Furthermore, travel time to a participant's usual source of medical care was explored for its relationship to these stages of stroke-risk factors and to investigate how travel time might influence the association between these factors and rural/urban status. No associations were identified for the main effects between the likelihood of being aware of, treated, or controlled for stroke-risk factors, and living in rural and urban settings. Drive time showed no relationship with these stages of stroke-risk factors, nor did it modify the effect rural or urban status had on the dependent variables. Disparities were noted for demographic, socioeconomic, and health behavioral traits for all three risk factors. This project made use of REGARDS study data sources to provide an understanding of stroke disparities for a certain geographic dimension. However, these data alone are unable to specifically identify rural and urban differences in stroke-risk factors and assess what effects access to health care has on the management of stroke-risk factors. The results from this investigation specify limited variability for management of these conditions by this study's measures of access to care. (Published By University of Alabama Libraries

Construction of estimation-equivalent second-order split-split-plot designs

In many experimental settings, some experimental factors are very hard to change or very expensive to change, some factors are hard to change, and some factors are easy to change, which usually leads to a split-split-plot design. In such a case, there are randomization restrictions in our experiments. If the data is analyzed as if it were a completely randomized design, the results could be misleading. The analysis of split-split-plot designs is more complicated relative to the completely randomized design, as generalized least squares (GLS) is recommended for estimating the factor effects, and restricted maximum likelihood (REML) is recommended for estimating the variance components. As an alternative, one can consider estimation-equivalent designs, wherein ordinary least squares (OLS) and GLS estimates of the factor effects are equivalent. These designs provide practical benefits from the perspective of design selection and estimation and are consistent with traditional response surface methods. Although much work has been done with respect to estimation-equivalent second-order split-plot designs, less emphasis has been placed on split-split-plot (and higher strata) designs of this type. My research is to derive the general conditions for achieving OLS-GLS equivalence and use these conditions to construct balanced and unbalanced estimation-equivalent second-order split-split-plot designs from the central composite design (CCD). (Published By University of Alabama Libraries