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151
Making interactive online visualizations with stata2leaflet and stata2d3
Grant, Robert
-
Stata User Group
-
2014
The last three years have seen explosive growth in the variety and sophistication of interactive online graphics. These are mostly implemented in the web language JavaScript, with the D3 (Data Driven Documents) library being the most popular and flexible at present. Leaflet is a mapping library...
Persistent link: https://www.econbiz.de/10010888636
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152
Transformation survival models
Marchenko, Yulia
-
Stata User Group
-
2014
The Cox proportional hazards model is one of the most popular methods for analyzing survival or failure-time data. The key assumption underlying the Cox model is that of proportional hazards. This assumption may often be violated in practice. Transformation survival models extend the Cox...
Persistent link: https://www.econbiz.de/10010888637
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153
-ctgov-: A suite of Stata commands for reporting trial results to ClinicalTrials.gov
Schumm, Phil
;
Karrison, Theodore
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Stata User Group
-
2014
In response to the 1997 Food and Drug Administration Modernization Act (FDAMA), the National Institutes of Health (NIH) established ClinicalTrials.gov, an online, publicly-accessible registry for clinical trials. The 2007 Food and Drug Administration Amendments Act (FDAAA) broadened the scope of...
Persistent link: https://www.econbiz.de/10010888638
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154
Computer simulation of patient flow through an operating suite
Clark, David
-
Stata User Group
-
2014
Operating room (OR) inefficiency is costly and stressful for patients and staff. To evaluate possible improvements, we simulated our OR and Recovery Room (RR) processes with Stata. We used hospital data (in long format) and parametric time-to-event regression (streg) to derive log-logistic...
Persistent link: https://www.econbiz.de/10010888639
Saved in:
155
Measuring Mobility
Nichols, Austin
-
Stata User Group
-
2014
Various measures of mobility using panel data are reviewed, with applications to measuring economic or social mobility in survey data. A variety of approaches are demonstrated.
Persistent link: https://www.econbiz.de/10010888640
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156
Estimating average treatment effects from observational data using teffects
Drukker, David
-
Stata User Group
-
2014
After reviewing the potential-outcome framework for estimating treatment effects from observational data, I will discuss how to estimate the average treatment effect and the average treatment effect on the treated by the regression-adjustment estimator, the inverse-probability-weighted...
Persistent link: https://www.econbiz.de/10010888641
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157
Optimal Interval Design for Phase I Oncology Clinical Trials
Fellman, Bryan
;
Yuan, Ying
-
Stata User Group
-
2014
The optimal interval design is a novel phase I trial design for finding the maximum tolerated dose (MTD). The optimal interval design casts dose finding as a sequential decision making problem for assigning an appropriate dose for each enrolled patient. The design optimizes the assignment of...
Persistent link: https://www.econbiz.de/10010888642
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158
A midas retouch regarding diagnostic meta-analysis
Dwamena, Ben Adarkwa
-
Stata User Group
-
2014
The talk describes recent updates for midas, a comprehensive and medically popular program for diagnostic test accuracy meta-analysis. A major change is that midas is now an estimation command and a wrapper for meglm of Stata 13 . The update allows more flexibility for specifying covariance...
Persistent link: https://www.econbiz.de/10010888643
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159
Small multiples, or the science and art of combining graphs
Cox, Nicholas
-
Stata User Group
-
2014
Good graphics often exploit a simple graphical design repeated for different parts of the data, which Edward R. Tufte dubbed the use of small multiples. In Stata small multiples are supported for different subsets of the data through by() or over() options of many graph commands: users can...
Persistent link: https://www.econbiz.de/10010888644
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160
Do-It-Yourself Multiple Imputation: Mode Effect Correction in a Public Opinion Survey
Kolenikov, Stanislav
-
Stata User Group
-
2014
In this talk, I am demonstrating how a multiple imputation procedure can be built by a user from scratch. The motivating example comes from a public opinion survey in which the sampled respondents were providing their responses on the web or by phone. As is known in survey methodology...
Persistent link: https://www.econbiz.de/10010888645
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