Download e-book for iPad: Analysis of categorical data with R by Christopher R. Bilder

By Christopher R. Bilder

ISBN-10: 1439855676

ISBN-13: 9781439855676

"We stay in a specific international! From a good or damaging affliction analysis to picking all goods that follow in a survey, results are often geared up into different types in order that humans can extra simply make feel of them. even if, reading info from express responses calls for really expert concepts past these realized in a primary or moment path in information. We o er this booklet to assist scholars and Read more...

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Table <- array ( data = c (57 , 142 , 200688 , 201087) , dim = c (2 ,2) , dimnames = list ( Treatment = c (" vaccine " , " placebo ") , Result = c (" polio " , " polio free ") ) ) > c . table Result Treatment polio polio free vaccine 57 200688 placebo 142 201087 Analyzing a binary response, part 1: introduction 39 > pi . hat . table <- c . table / rowSums ( c . table ) > pi . hat . 9992943 > pi . hat1 <- pi . hat . table [1 ,1] > pi . hat2 <- pi . hat . table [2 ,1] > round ( pi . hat1 / pi . 4024 > round (1/( pi .

Table [1 ,1] > pi . hat2 <- pi . hat . table [2 ,1] > # Wald > var . wald <- pi . hat1 *(1 - pi . hat1 ) / sum ( c . table [1 ,]) + pi . hat2 *(1 - pi . hat2 ) / sum ( c . table [2 ,]) > pi . hat1 - pi . hat2 + qnorm ( p = c ( alpha /2 , 1 - alpha /2) ) * sqrt ( var . 06227017 > > > > # Agresti - Caffo pi . tilde1 <- ( c . table [1 ,1] + 1) / ( sum ( c . table [1 ,]) + 2) pi . tilde2 <- ( c . table [2 ,1] + 1) / ( sum ( c . table [2 ,]) + 2) var . AC <- pi . tilde1 *(1 - pi . tilde1 ) / ( sum ( c .

Samples , size = n , prob = pi ) pi . hat <- w / n var . wald <- pi . hat *(1 - pi . hat ) / n lower <- pi . hat - qnorm ( p = 1 - alpha /2) * sqrt ( var . wald ) upper <- pi . hat + qnorm ( p = 1 - alpha /2) * sqrt ( var . wald ) data . frame ( lower , upper ) [1:10 ,] w pi . 878 Again, we are using much of the same code as in the past. 157 is within each of the intervals. 157, so the corresponding value of save is 0. 878. 157. In this relatively simple simulation problem, we already know that the intervals for w = 4, .

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Analysis of categorical data with R by Christopher R. Bilder


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