search for: b1x1

I have a logit model with about 10 predictors and I am trying to plot the probability curve for the model. Y=1 = 1 / 1+e^-z where z=B0 + B1X1 + ... + BnXi If the model had only one predictor, I know to do something like below. mod1 = glm(factor(won) ~ as.numeric(bid), data=mydat, family=binomial(link="logit")) all.x <- expand.grid(won=unique(won), bid=unique(bid)) y.hat.new <- predict(mod1, newdata=all.x, type="re...

Forgive me if this is a trivial question, but I couldn't find it an answer in former forums. I'm trying to reproduce some SAS results where they set two parameters equal. For example: y = b1X1 + b2X2 + b1X3 Notice that the variables X1 and X3 both have the same slope and the intercept has been removed. How do I get an estimate of this regression model? I know how to remove the intercept ("-1" somewhere after the tilde). But how about setting parameters equal? I have used the c...

Hi all, Can you please tell me what is the problem here. My regression eq is y = B0 + B1X1 +B2X2 +e And i am interested in coefficient B1 I am doing regression with two cases: 1) reg<-lm(y ~ X1 + X2, sam) where sam is the data 2) reg<-lm(y ~ X1 + X2, sam, na.action= na.exclude) . I have missing values in X1 but the values of coefficient is not consistent in two cases. Actuall...

Dear All, I am currently working with the coxph function within the package survival. I have the model h_ij = h_0(t) exp(b1x1 + b2x2) where the indicator variables are as follows: x1 x2 VPS 0 0 LTG 1 0 TPM 0 1 [[alternative HTML version deleted]]

Hi everyone: ¡¡I am new to R and I have a really basic question. I have already got a generalized linear model from some dataset, say y=b0 + b1X1 + b2X2. Then I want to get the value of y provided, say, X1=1, X2=2. And the confidence Intervals of this y. I know I can just calculate that since I know the model already. But is there some code that can calculate those automatically? Thank you very much! [[alternative HTML...

Hi everyone, I'm trying to perform a linear regression y = b1x1 + b2x2 + b3x3 + b4x4 + b5x5 while constraining the coefficients such that -3 <= bi <= 3, and the sum of bi =1. I've searched R-help and have found solutions for constrained regression using quadratic programming (solve.QP) where the coefficients are between 0 and 1 and sum to 1, but...

Hello, I am trying to learn how to perform Multiple Regression Analysis in R. I decided to take a simple example given in this PDF: http://www.utdallas.edu/~herve/abdi-prc-pretty.pdf I created a small CSV called, students.csv that contains the following data: s1 14 4 1 s2 23 4 2 s3 30 7 2 s4 50 7 4 s5 39 10 3 s6 67 10 6 Col headers: Student id, Memory span(Y), age(X1), speech rate(X2) Now

Dear R-Help-List, I was wondering if anyone had experience simulating case-control data in R? I've been looking through literature, and found that the main examples make heavy parametric assumptions on the distributions of the exposure (E), covariates (Z), and disease status (D). I would appreciate any guidance toward resources/examples/literature that simulate case-control data with fewer

Good day R-listers, My question is more a statistical question than an R related question, so please bear with me i'm currently applying the chow test of poolability in fact i'm working with panel N=17 T=5 , and my model looks like this : Yit= a0+B1X1+B2X2+B3X3+B4X4+eit My question is the following when i'm Testing for the equality of the coefficients of the unpooled data (the last stage) many of my constraints get dropped, this indeed impact the degree of freedom of my F statistic , and would like to understand the reason? is this becau...

Hi all. In a GLM in which g(mu) = b0 + b1X1 + b2X2 + b3X3 + b4X4 + b5X5 + b6X6 + b7X7, if I want to test if b1 + b5 = b2 + b6, I can use the contrast package or multicomp package. How can I do a similar test if I am fitting a GAMLSS using the gamlss package? Thank you for your help. Gustavo

Hi, This is not an R question, but I've seen opinions given on non R topics, so I wanted to give it a try. :) How would one treat a variable that was measured once, but is known to fluctuate a lot? For example, I want to include a hormone in my regression as an explanatory variable. However, this hormone varies in its levels throughout a day. Nevertheless, its levels differ substantially