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Summary judgment in federal courts has been widely regarded as an initially underused procedural device that was revitalized by the 1986 Supreme Court trilogy of Celotex, Anderson, and Matsushita. Some recent commentators believe summary judgment activity has expanded to the point that it threatens the right to trial. We examined summary judgment practice in six federal district courts during six time periods over 25 years (1975–2000), extracting information on summary judgment practice from 15,000 docket sheets in random samples of terminated cases. We found that when we controlled for changes over time in the types of cases being filed, the likelihood that a case contained one or more motions for summary judgment increased before the Supreme Court trilogy, from approximately 12 percent in 1975 to 17 percent in 1986, and has remained fairly steady at approximately 19 percent since that time. The increase prior to the 1986 trilogy and the modest changes subsequent to the trilogy would be unexpected by many legal commentators. Although summary judgment motions have increased over this 25-year period, this increase reflects, at least in part, increased filings of civil rights cases, which have always experienced a high rate of summary judgment motions. Surprisingly, no statistically significant changes over time were found in the outcome of defendants’ or plaintiffs’ summary judgment motions, again after controlling for differences across courts and types of cases. These findings call into question the interpretation that the trilogy led to expansive increases in summary judgment. Our analysis suggests, instead, that changes in civil rules and federal case-management practices prior to the trilogy may have been more important in bringing about changes in summary judgment practice.

Good quantitative evidence does not require large, aggregate group designs. The authors describe ground-breaking work in managing the conceptual and practical demands in developing meta-analytic strategies for single subject designs in an effort to add to evidence-based practice.

When analyzing a contingency table, the most frequently used procedure is to test the association between variables using a chi-square test of independence. If the variables are not independent, no further testing is typically done. However, the chi-square can be decomposed, or partitioned, into components to test hypotheses concerning the nature of the differences among categories of the variables. One can determine which categories of one variable are (and are not) the same in their relation to the other variable. Keywords: chi-square; decomposition; contingency table; categorical data; partition; nonstandard model

Objectives: The bidirectional relationship between periodontitis and diabetes suggests that the dental visit may offer a largely untapped opportunity to screen for undiagnosed diabetes. To better examine this potential opportunity, data from the National Health and Nutrition Examination Survey (NHANES) 2003-2004 were used to determine if a larger proportion of patients with periodontal disease as compared with those without periodontitis would be recommended for screening according to American Diabetes Association (ADA) guidelines. The data were also used to determine whether at-risk individuals with periodontitis visited a dental professional recently, so that they could avail themselves of this opportunity for screening, if offered. Methods: Data to perform these analyses were collected from 2,923 subjects aged 20 and older who reported that they were never told that they had diabetes, had a periodontal examination, and had sufficient data to compute body mass index. Descriptive statistics, t-tests, and chi-square analyses that compared those with and without periodontitis were extrapolated to the US population. Results: A total of 62.9 percent of those without periodontitis and 93.4 percent of those with periodontal disease met ADA guidelines for diabetes screening. Of those at-risk with periodontal disease, 33.9 percent had seen a dentist in the past 6 months, 50 percent in the past year, and 60.4 percent in the past 2 years. Conclusions: As almost all individuals with periodontitis would have been recommended for diabetes screening, and many at-risk persons with periodontal disease recently visited a dentist, our data suggest that the dental visit provides an important potential venue for this screening.

Modeling the process by which participants are selected into groups, rather than adjusting for preexisting group differences, provides the basis for several new approaches to the analysis of data from nonrandomized studies.

With perfect information from flawlessly designed and executed evaluations of social programs in short supply, evaluators are urged to look to gathering many kinds of evidence and analyzing it by multiple methods to reduce the incidence of erroneous conclusions.

Assessment of the value of diagnostic indicators such as symptoms and laboratory tests results from calculation of the sensitivity and specificity of the indicators. Knowledge of the rate of occurrence of the disease allows for additional calculations of the error rates in using an indicator. These calculations are accurate only when the data on which they are based are reliable. If the diagnosis, which is used as the criterion for computing the sensitivity and specificity, is not accurate, then the resulting calculations will be in error. We show how a statistical method, latent class analysis, allows for the estimation of the characteristics of indicators even when an accurate diagnosis is unavailable. In addition, the method deals with several indicators at once, and provides a way to combine the information from all the indicators to make a diagnosis.