Nurses\u27 Alumnae Association Bulletin, May 1963

President\u27s Letter Alumnae Meetings, 1962 Building Fund Mediocrity Hospital Report Alumnae Notes Social Committee Student Activities Marriages, New Arrivals and Necrology Annual Giving Fund Driv

Numerical Simulations of Soil Liquefaction using Stochastic Input Parameters

The influence of spatial variability of soil properties on the results of numerical simulations of dynamically induced pore water pressure is addressed. Random media of NSPT values are generated based on in situ test results. The soil geomechanical properties are evaluated at each location, function of the NSPT values, and finite element simulations of the behavior of a horizontally layered soil subjected to seismic loading are performed. The influence of : (1) assumed distribution of the underlying random variable, (2) scale of fluctuation, and (3) finite element mesh size are discussed in terms of predicted liquefaction index and excess pore pressure build-up

Adjusting for verification bias in diagnostic accuracy measures when comparing multiple screening 2 tests - an application to the IP1-PROSTAGRAM study

Introduction Novel screening tests used to detect a target condition are compared against either a reference standard or other existing screening methods. However, as it is not always possible to apply the reference standard on the whole population under study, verification bias is introduced. Statistical methods exist to adjust estimates to account for this bias. We extend common methods to adjust for verification bias when multiple tests are compared to a reference standard using data from a prospective double blind screening study for prostate cancer. Methods Begg and Greenes method and multiple imputation are extended to include the results of multiple screening tests which determine condition verification status. These two methods are compared to the complete case analysis using the IP1-PROSTAGRAM study data. IP1-PROSTAGRAM used a paired84 cohort double-blind design to evaluate the use of imaging as alternative tests to screen for prostate 85 cancer, compared to a blood test called prostate specific antigen (PSA). Participants with positive imaging (index) and/or PSA (control) underwent a prostate biopsy (reference). Results When comparing complete case results to Begg and Greenes and methods of multiple imputation there is a statistically significant increase in the specificity estimates for all screening tests. Sensitivity estimates remained similar across the methods, with completely overlapping 95% confidence intervals. Negative predictive value (NPV) estimates were higher when adjusting for verification bias, compared to complete case analysis, even though the 95% confidence intervals overlap. Positive predictive value (PPV) estimates were similar across all methods. Conclusion Statistical methods are required to adjust for verification bias in accuracy estimates of screening tests. Expanding Begg and Greenes method to include multiple screening tests can be computationally intensive, hence multiple imputation is recommended, especially as it can be modified for low prevalence of the target condition

Nurses\u27 Alumnae Association Bulletin, December 1968

President\u27s Message Officers and Committee Chairman Financial Report Report to Alumnae Association Annual Report to Alumnae Association School of Practical Nursing Report Student Activities Nursing Service Staff Association Letter from Vietnam Resume of Alumnae Meetings Ways and Means Report Social Committee Building Fund Report Bulletin Committee Report Class News Notice