Effect of nonnormal random components on level and power in group-randomized trials

The use of group-randomized trials is particularly widespread in the evaluation of health care, educational, and screening strategies. Group-randomized trials represent a subset of a larger class of designs often labeled nested, hierarchical, or multilevel and are characterized by the randomization of intact social units or groups, rather than individuals. The application of random effects models to group-randomized trials requires the specification of fixed and random components of the model. The underlying assumption is usually that these random components are normally distributed. This research is intended to determine if the Type I error rate and power are affected when the assumption of normality for the random component representing the group effect is violated. ^ In this study, simulated data are used to examine the Type I error rate, power, bias and mean squared error of the estimates of the fixed effect and the observed intraclass correlation coefficient (ICC) when the random component representing the group effect possess distributions with non-normal characteristics, such as heavy tails or severe skewness. The simulated data are generated with various characteristics (e.g. number of schools per condition, number of students per school, and several within school ICCs) observed in most small, school-based, group-randomized trials. The analysis is carried out using SAS PROC MIXED, Version 6.12, with random effects specified in a random statement and restricted maximum likelihood (REML) estimation specified. The results from the non-normally distributed data are compared to the results obtained from the analysis of data with similar design characteristics but normally distributed random effects. ^ The results suggest that the violation of the normality assumption for the group component by a skewed or heavy-tailed distribution does not appear to influence the estimation of the fixed effect, Type I error, and power. Negative biases were detected when estimating the sample ICC and dramatically increased in magnitude as the true ICC increased. These biases were not as pronounced when the true ICC was within the range observed in most group-randomized trials (i.e. 0.00 to 0.05). The normally distributed group effect also resulted in bias ICC estimates when the true ICC was greater than 0.05. However, this may be a result of higher correlation within the data. ^

First Trimester Screening and its Impact on Uptake of Diagnostic Testing

Introduction: First Trimester Screening (FTS) combines maternal age with fetal nuchal translucency (NT) and maternal analytes to identify pregnancies at an increased risk for Down syndrome and trisomy 18. Though the accuracy of this screening is high, it cannot replace the conclusive accuracy of prenatal diagnostic testing (PDT). Since FTS has been available, a decrease in the number of women who pursue PDT has been observed. This study sought to determine if there has been a significant change in the amount of PDT performed in our clinics, if the type of FTS result affects the patient’s decision regarding PDT, and what the patient’s intentions are regarding PDT. Material and Methods: A database review was performed for the two years prior and the two years after the January 2007 American College of Obstetricians and Gynecologists (ACOG) guidelines regarding FTS were issued. We compared the number of women who were AMA and the number of women who were AMA and had PDT between those time periods. We also determined the number of positive and negative FTS results, and determined how many of those patients had PDT. Finally, we surveyed our patients and referring physicians to determine: what the patient understands about FTS, what the patient’s intentions are regarding FTS, and how physicians present the option of FTS to their patients. Results: We determined that there was a 19.6% decrease in the amount of PDT performed when we compared the two time periods at our three specified clinics. Many of our patients were against having PDT prior to their genetic counseling session, but after they received genetic counseling, 76% of our population became open to the possibility of having PDT. Conclusion: Similar to previous studies, we determined that there has been a significant decrease in the number of PDT procedures performed at our clinics, which coincides with the release of the January 2007 ACOG statement regarding FTS. While our patients regarded FTS as a way to gain early information about their pregnancy in a non-invasive manner, they also stated they would use their results as a way to aid in their decision regarding PDT.

Development and testing of a procedure for systematically assigning gestational age for clinical and research use

A graphing method was developed and tested to estimate gestational ages pre-and postnatally in a consistent manner for epidemiological research and clinical purposes on feti/infants of women with few consistent prenatal estimators of gestational age. Each patient's available data was plotted on a single page graph to give a comprehensive overview of that patient. A hierarchical classification of gestational age determination was then applied in a systematic manner, and reasonable gestational age estimates were produced. The method was tested for validity and reliability on 50 women who had known dates for their last menstrual period or dates of conception, and multiple ultrasound examinations and other gestational age estimating measures. The feasibility of the procedure was then tested on 1223 low income women with few gestational age estimators. The graphing method proved to have high inter- and intrarater reliability. It was quick, easy to use, inexpensive, and did not require special equipment. The graphing method estimate of gestational age for each infant was tested against the last menstrual period gestational age estimate using paired t-Tests, F tests and the Kolmogorov-Smirnov test of similar populations, producing a 98 percent probability or better that the means and data populations were the same. Less than 5 percent of the infants' gestational ages were misclassified using the graphing method, much lower than the amount of misclassification produced by ultrasound or neonatal examination estimates. ^