Before Memmo my notes were scattered across PDFs. Now a workspace pulls everything into one place — I see exactly what's still left to study.
This unique reference/text provides an understanding of nonparametric and quasi parametric (regression) methods to analyze survivorship data in clinical studies emphasizing the interpretation and reasoning behind these methods.
Written for clinicians, as well as biostatisticians, Survivorship Analysis for Clinical Studies justifies each new methodology presented and clarifies its relationship to preceding material. It describes and explains established methods for summarizing the results of the majority of single-clinic survivorship studies, comparing two or more survival processes, and examining the effects of covariates on survival.
Including a diskette containing programs for computing confidence bands for survival curves, this book serves as a timely reference for biostatisticians, clinicians engaged in clinical trials, pharmacologists involved in new drug testing, epidemiologists, and biomedical engineers, and as a superb text for upper-level undergraduate and graduate students, as well as participants in professional seminars on survivorship data analysis in clinical settings.
Before Memmo my notes were scattered across PDFs. Now a workspace pulls everything into one place — I see exactly what's still left to study.
Memmo's summaries are gold before exams. I don't have to re-read 800 pages two weeks before — just the important parts.
The AI chat has saved me the night before an exam more than once. I just keep asking until I get it — no waiting on a study group to reply.
The quizzes hit exactly what I need to know. Memmo tracks what I get stuck on — so I only practice what's worth it.
Flashcards with spaced repetition are magic. Memmo knows when I'm about to forget something and brings it back.
The AI podcasts are my favorite. I listen on my way to school and get a recap without sitting at a computer.
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