Question: "It is difficult for me to comprehend the difference between standard deviation and variance after having good amount of reading. Can you pl help me." (from LinkedIn)
My answer:
Variability
Show Standard Deviation
Calculate Variance
Thursday, October 13, 2011
Friday, July 29, 2011
Ramblings about clinical statistics
When I started doing statistics for psychiatric clinical trials, I visualized my role as being on the top of a pyramid: standing on all the information & data from the study, I was privileged to 1st see & understand the results of the study.
Later, I visualized my role as being at the bottom of a funnel: each of thousands of numbers coming out of the funnel was the distillation of a tragic story entering the funnel, a summarization of decades of suffering for a patient and their family.
(I recently wrote this on Facebook)
Later, I visualized my role as being at the bottom of a funnel: each of thousands of numbers coming out of the funnel was the distillation of a tragic story entering the funnel, a summarization of decades of suffering for a patient and their family.
(I recently wrote this on Facebook)
Friday, April 29, 2011
Simulating randomized withdrawal studies for prediction & management
Title of talk: Signs of the Timings: Predicting Time of Completion in Multiphase Survival Trials
Paper as published in the conference proceedings: Predicting Time of Completion in Multiphase Survival Trials
Abstract:
Studying maintenance of clinical effect typically requires clinical response for a minimum amount of time on treatment before randomization. If randomized, patients are then followed until treatment failure or withdrawal, and the trial halted after a pre-specified number of events. For ethical and cost reasons it is desirable to minimize the number of patients enrolled and randomized, and to predict the time of the last event under multiple scenarios.
We describe a data-driven stochastic simulation for two such trials in which: Each phase is modeled as a competing event process; Distributions of event times are derived from Kaplan-Meier survival curves from available data; Parameter uncertainty is modeled based on K-M survival estimates; Withdrawals and events occur at similar overall rates, though at different times; Predictions are updated as information is accrued.
Presented to:
Joint Statistical Meeting of the American Statistical Association
Seattle, WA
August, 2006
Delaware Chapter of the American Statistical Association
Dinner Meeting: September 21, 2006
Speaker: Dennis E. Sweitzer
AstraZeneca
Paper as published in the conference proceedings: Predicting Time of Completion in Multiphase Survival Trials
Abstract:
Studying maintenance of clinical effect typically requires clinical response for a minimum amount of time on treatment before randomization. If randomized, patients are then followed until treatment failure or withdrawal, and the trial halted after a pre-specified number of events. For ethical and cost reasons it is desirable to minimize the number of patients enrolled and randomized, and to predict the time of the last event under multiple scenarios.
We describe a data-driven stochastic simulation for two such trials in which: Each phase is modeled as a competing event process; Distributions of event times are derived from Kaplan-Meier survival curves from available data; Parameter uncertainty is modeled based on K-M survival estimates; Withdrawals and events occur at similar overall rates, though at different times; Predictions are updated as information is accrued.
Presented to:
Joint Statistical Meeting of the American Statistical Association
Seattle, WA
August, 2006
Delaware Chapter of the American Statistical Association
Dinner Meeting: September 21, 2006
Speaker: Dennis E. Sweitzer
AstraZeneca
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