Slope estimation in a parametric measurement error model: A simulation study

In regression analysis, covariate measurement error occurs in many applications. The error-prone covariates are often referred to as latent variables. In this proposed study, we extended the study of Chan et al. (2008) on recovering latent slope in a simple regression model to that in a multiple regression model. We presented an approach that applied the Monte Carlo method in the Bayesian framework to the parametric regression model with the measurement error in an explanatory variable. The proposed estimator applied the conditional expectation of latent slope given the observed outcome and surrogate variables in the multiple regression models. A simulation study was presented showing that the method produces estimator that is efficient in the multiple regression model, especially when the measurement error variance of surrogate variable is large.^

The number and timing of time -dependent covariate measurements for the Cox regression model

The problem of analyzing data with updated measurements in the time-dependent proportional hazards model arises frequently in practice. One available option is to reduce the number of intervals (or updated measurements) to be included in the Cox regression model. We empirically investigated the bias of the estimator of the time-dependent covariate while varying the effect of failure rate, sample size, true values of the parameters and the number of intervals. We also evaluated how often a time-dependent covariate needs to be collected and assessed the effect of sample size and failure rate on the power of testing a time-dependent effect.^ A time-dependent proportional hazards model with two binary covariates was considered. The time axis was partitioned into k intervals. The baseline hazard was assumed to be 1 so that the failure times were exponentially distributed in the ith interval. A type II censoring model was adopted to characterize the failure rate. The factors of interest were sample size (500, 1000), type II censoring with failure rates of 0.05, 0.10, and 0.20, and three values for each of the non-time-dependent and time-dependent covariates (1/4,1/2,3/4).^ The mean of the bias of the estimator of the coefficient of the time-dependent covariate decreased as sample size and number of intervals increased whereas the mean of the bias increased as failure rate and true values of the covariates increased. The mean of the bias of the estimator of the coefficient was smallest when all of the updated measurements were used in the model compared with two models that used selected measurements of the time-dependent covariate. For the model that included all the measurements, the coverage rates of the estimator of the coefficient of the time-dependent covariate was in most cases 90% or more except when the failure rate was high (0.20). The power associated with testing a time-dependent effect was highest when all of the measurements of the time-dependent covariate were used. An example from the Systolic Hypertension in the Elderly Program Cooperative Research Group is presented. ^

Evaluation of the causal pathways through which subjective norms influence mammography intention and stage of change in a national sample of women veterans

Few studies have investigated causal pathways linking psychosocial factors to each other and to screening mammography. Conflicting hypotheses exist in the theoretic literature regarding the role and importance of subjective norms, a person's perceived social pressure to perform the behavior and his/her motivation to comply. The Theory of Reasoned Action (TRA) hypothesizes that subjective norms directly affect intention; while the Transtheoretical Model (TTM) hypothesizes that attitudes mediate the influence of subjective norms on stage of change. No one has examined which hypothesis best predicts the effect of subjective norms on mammography intention and stage of change. Two statistical methods are available for testing mediation, sequential regression analysis (SRA) and latent variable structural equation modeling (LVSEM); however, software to apply LVSEM to dichotomous variables like intention has only recently become available. No one has compared the methods to determine whether or not they yield similar results for dichotomous variables. ^ Study objectives were to: (1) determine whether the effect of subjective norms on mammography intention and stage of change are mediated by pros and cons; and (2) compare mediation results from the SRA and LVSEM approaches when the outcome is dichotomous. We conducted a secondary analysis of data from a national sample of women veterans enrolled in Project H.O.M.E. (H&barbelow;ealthy O&barbelow;utlook on the M&barbelow;ammography E&barbelow;xperience), a behavioral intervention trial. ^ Results showed that the TTM model described the causal pathways better than the TRA one; however, we found support for only one of the TTM causal mechanisms. Cons was the sole mediator. The mediated effect of subjective norms on intention and stage of change by cons was very small. These findings suggest that interventionists focus their efforts on reducing negative attitudes toward mammography when resources are limited. ^ Both the SRA and LVSEM methods provided evidence for complete mediation, and the direction, magnitude, and standard errors of the parameter estimates were very similar. Because SRA parameter estimates were not biased toward the null, we can probably assume negligible measurement error in the independent and mediator variables. Simulation studies are needed to further our understanding of how these two methods perform under different data conditions. ^

Epidemiologic and methodological issues in serial measurements of blood pressure: The blood pressure study in Mexican children

The Blood Pressure Study in Mexican Children (BPSMC) is a short term longitudinal study of serial blood pressure collected in three observation periods by standardized examinations of 233 female children, 10 to 12 years of age, enrolled in public and private primary schools in Tlalpan, Mexico. Study objectives were: (1) to describe from baseline information the distribution and relationship of blood pressure to age and selected anthropometric factors, as well as to compare the BPSMC results with other blood pressure studies, (2) to examine the sources and amount of variation present in serial blood pressure of 123 children, and (3) to evaluate observer performance by means of intra- and inter-observer variability.^ Stepwise regression results from baseline revealed that of all anthropometric factors and age, weight was the best predictor for blood pressure.^ The results of serial blood pressure measurements show that, besides the known sources of blood pressure variability (subject, day, reading), the physiologic event of menarche has an important bearing upon the variability and characterization of blood pressure in young girls. The assessment of the effects of blood pressure variability and reliability upon the design and analysis of epidemiologic studies, became apparent among post-menarcheal girls; where blood pressure measurements taken from them have low reliability. Research is needed to propose alternatives for assessing blood pressure during puberty.^ Finally, observer performance of blood pressure and anthropometry were evaluated. Anthropometric measurements had reliabilities in excess of R = 0.96. Acceptable reliabilities (R = 0.88 to 0.95) were obtained for systolic and diastolic (phase 4 and 5) blood pressures. The BPSMC showed a 50 percent decrease in measurement error from the first to the third observation periods. ^

Evaluation of the Hosmer -Lemeshow global goodness -of-fit statistic for mixed variable logistic regression models

The performance of the Hosmer-Lemeshow global goodness-of-fit statistic for logistic regression models was explored in a wide variety of conditions not previously fully investigated. Computer simulations, each consisting of 500 regression models, were run to assess the statistic in 23 different situations. The items which varied among the situations included the number of observations used in each regression, the number of covariates, the degree of dependence among the covariates, the combinations of continuous and discrete variables, and the generation of the values of the dependent variable for model fit or lack of fit.^ The study found that the $\rm\ C$g* statistic was adequate in tests of significance for most situations. However, when testing data which deviate from a logistic model, the statistic has low power to detect such deviation. Although grouping of the estimated probabilities into quantiles from 8 to 30 was studied, the deciles of risk approach was generally sufficient. Subdividing the estimated probabilities into more than 10 quantiles when there are many covariates in the model is not necessary, despite theoretical reasons which suggest otherwise. Because it does not follow a X$\sp2$ distribution, the statistic is not recommended for use in models containing only categorical variables with a limited number of covariate patterns.^ The statistic performed adequately when there were at least 10 observations per quantile. Large numbers of observations per quantile did not lead to incorrect conclusions that the model did not fit the data when it actually did. However, the statistic failed to detect lack of fit when it existed and should be supplemented with further tests for the influence of individual observations. Careful examination of the parameter estimates is also essential since the statistic did not perform as desired when there was moderate to severe collinearity among covariates.^ Two methods studied for handling tied values of the estimated probabilities made only a slight difference in conclusions about model fit. Neither method split observations with identical probabilities into different quantiles. Approaches which create equal size groups by separating ties should be avoided. ^

Activity of anidulafungin in a murine model of Candida krusei infection: evaluation of mortality and disease burden by quantitative tissue cultures and measurement of serum (1,3)-beta-D-glucan levels.

Experience with anidulafungin against Candida krusei is limited. Immunosuppressed mice were injected with 1.3 x 10(7) to 1.5 x 10(7) CFU of C. krusei. Animals were treated with saline, 40 mg/kg fluconazole, 1 mg/kg amphotericin B, or 10 and 20 mg/kg anidulafungin for 5 days. Anidulafungin improved survival and significantly reduced the number of CFU/g in kidneys and serum beta-glucan levels.

Policy analysis of Texas Senate Bill 532 and the regulation of nurse practitioners in the convenience care model

Background. Retail clinics, also called convenience care clinics, have become a rapidly growing trend since their initial development in 2000. These clinics are coupled within a larger retail operation and are generally located in "big-box" discount stores such as Wal-mart or Target, grocery stores such as Publix or H-E-B, or in retail pharmacies such as CVS or Walgreen's (Deloitte Center for Health Solutions, 2008). Care is typically provided by nurse practitioners. Research indicates that this new health care delivery system reduces cost, raises quality, and provides a means of access to the uninsured population (e.g., Deloitte Center for Health Solutions, 2008; Convenient Care Association, 2008a, 2008b, 2008c; Hansen-Turton, Miller, Nash, Ryan, Counts, 2007; Salinsky, 2009; Scott, 2006; Ahmed & Fincham, 2010). Some healthcare analysts even suggest that retail clinics offer a feasible solution to the shortage of primary care physicians facing the nation (AHRQ Health Care Innovations Exchange, 2010). ^ The development and performance of retail clinics is heavily dependent upon individual state policies regulating NPs. Texas currently has one of the most highly regulated practice environments for NPs (Stout & Elton, 2007; Hammonds, 2008). In September 2009, Texas passed Senate Bill 532 addressing the scope of practice of nurse practitioners in the convenience care model. In comparison to other states, this law still heavily regulates nurse practitioners. However, little research has been conducted to evaluate the impact of state laws regulating nurse practitioners on the development and performance of retail clinics. ^ Objectives. (1). To describe the potential impact that SB 532 has on retail clinic performance. (2). To discuss the effectiveness, efficiency, and equity of the convenience care model. (3). To describe possible alternatives to Texas' nurse practitioner scope of practice guidelines as delineated in Texas Senate Bill 532. (4). To describe the type of nurse practitioner state regulation (i.e. independent, light, moderate, or heavy) that best promotes the convenience care model. ^ Methods. State regulations governing nurse practitioners can be characterized as independent, light, moderate, and heavy. Four state NP regulatory types and retail clinic performance were compared and contrasted to that of Texas regulations using Dunn and Aday's theoretical models for conducting policy analysis and evaluating healthcare systems. Criteria for measurement included effectiveness, efficiency, and equity. Comparison states were Arizona (Independent), Minnesota (Light), Massachusetts (Moderate), and Florida (Heavy). ^ Results. A comparative states analysis of Texas SB 532 and alternative NP scope of practice guidelines among the four states: Arizona, Florida, Massachusetts, and Minnesota, indicated that SB 532 has minimal potential to affect the shortage of primary care providers in the state. Although SB 532 may increase the number of NPs a physician may supervise, NPs are still heavily restricted in their scope of practice and limited in their ability to act as primary care providers. Arizona's example of independent NP practice provided the best alternative to affect the shortage of PCPs in Texas as evidenced by a lower uninsured rate and less ED visits per 1,000 population. A survey of comparison states suggests that retail clinics thrive in states that more heavily restrict NP scope of practice as opposed to those that are more permissive, with the exception of Arizona. An analysis of effectiveness, efficiency, and equity of the convenience care model indicates that retail clinics perform well in the areas of effectiveness and efficiency; but, fall short in the area of equity. ^ Conclusion. Texas Senate 532 represents an incremental step towards addressing the problem of a shortage of PCPs in the state. A comparative policy analysis of the other four states with varying degrees of NP scope of practice indicate that a more aggressive policy allowing for independent NP practice will be needed to achieve positive changes in health outcomes. Retail clinics pose a temporary solution to the shortage of PCPs and will need to expand their locations to poorer regions and incorporate some chronic care to obtain measurable health outcomes. ^