similar to: Help- extracting values

Dear All: I create a file named :"P_Value" with only one simple function: P_Value <- function( Table ) { S = fisher.test(Table, alternative = "two.sided"); return(S$p.value); } However, it seems that it's impossible to use this function directly, because no matter where I save this file, R always reports

Dear R Experts, I am attempting to run a mixed effects model on a within-subjects repeated measures design, but I am unsure if I am doing it properly. I was hoping that someone would be able to offer some guidance. There are 5 independent variables (subject, condition, difficulty, repetition) and 1 dependent measure (value). Condition and difficulty are fixed effects and have 3 levels each

Hi, I am using an if else statement inside a function ?. If I use that function I have no problems ?. If I use the function with the if else statement inside a second function I get the following waring: Warning message: In if (pval == 0) p_value <- "< 2.2e-16" else p_value <- pval : the condition has length> 1 and only the first element will be used Using the second

Hello Friends, I am new to R and stuck with a problem. i have two columns drug_A and drug_B, i have plotted a scatter plot using the ggplot2 function. My problem is with the third column, it is the p-value column. I want to color and size points differently based on the p_value, the p_value range is between 0<0.0001< 0.001<0.05<1. I used a script using the ifelse loop, but it

Buena tarde, Estoy llevando a cabo un trabajo y no encuentro la forma de llenar una matriz con el p_value y un estadístico calculado. Un poco mas detallado, tengo muestras aleatorias, calculo por ejemplo la prueba t, wilcoxon, etc y requiero llevar por una parte los p_value de k muestras a una matriz creada anteriormente y por otro lado el valor del estadístico de las mismas k muestras a otra

Hola, Bueno, puedes hacer el cálculo de una forma mucho más compacta y rápida. Esta forma es especialmente recomendable cuando tienes muchas columnas y muchas filas. > library(data.table) > myDT <- as.data.table(mtcars) > myDTlong <- melt(myDT, measure.vars=1:ncol(myDT)) > myDTlong[ , list(p_value = shapiro.test(value)$p.value, v_stat = shapiro.test(value)$statistic) , by

Buen día estimados Estoy tratando de hacer un tibble con los resultados de un apply que se muestran en la consola que me da R, no estoy seguro si eso se pueda hacer, pero me gustaría organizar los resultados de esa manera. mi código es: data("mtcars") Mtcars_matriz <- as.matrix(mtcars) apply(Mtcars_matriz, MARGIN =2, FUN = shapiro.test) DF2 <- tibble(Variable = NA, W = NA, Pvalue =

Hi. how can i insert the value of p_value from KS.test into vector? Regards, Irit. -- View this message in context: http://r.789695.n4.nabble.com/retrieveing-value-from-KS-test-tp4663439.html Sent from the R help mailing list archive at Nabble.com.

This was working a few weeks ago, but perhaps the package has been updated since then. model.1 <- lrm(response ~ p_value, data=c_abl_oncogene_1_RTK) When I run the following command . . . . prediction.1 <- predict(model.1, type=c("fitted")) I get the following error message. . . . Error in predictDesign(object, ..., type = "lp", se.fit = FALSE) : could not find

Hi, I'm trying to figure out how anova works in R by translating the examples in Sokal And Rohlf's (1995 3rd edition) Biometry. I've hit a snag with planned comparisons, their box 9.4 and section 9.6. It's a basic anova design: treatment <- factor(rep(c("control", "glucose", "fructose", "gluc+fruct",

Hi All, I was wondering if someone could help me to solve this issue with lmer. In order to understand the best mixed effects model to fit my data, I compared the following options according to the procedures specified in many papers (i.e. Baayen <http://www.google.it/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0CDsQFjAA

Hi, I have been examining large data and need to do simple linear regression with the data which is grouped based on the values of a particular attribute. For instance, consider three columns : ID, x, y, and I need to regress x on y for each distinct value of ID. Specifically, for the set of data corresponding to each of the 4 values of ID (76,111,121,168) in the below data, I should invoke

Starting with data from a microarray experiment and I would like to analyse the influence of two factors (age, treatment) on gene expression. Looking through the r-help archives and the web I tried the following: I put my data in a dataframe similar to this one: > example.df <- as.data.frame(matrix(data=runif(32,100,1000), nrow=4, ncol=4)) > example.df <-

Dear R-help,   Chi Square Test for Goodness of Fit     Problem Faced :   I have got a discrete data as given below (R script)   No_of_Frauds <-c 1,1,1,1,1,1,1,1,1,2,1,1,1,1,1,1,2,1,2,2,2,1,1,2,1,1,1,1,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,5,1,2,1,1,1,1,1,1,1,3,2,1,1,1,2,1,1,2,1,1,1,1,1,2,1,3,1,2,1,2,14,2,1,1,38,3,3,2,44,1,4,1,4,1,2,2,1,3)   I am trying to fit

Dear R-help, ? ? Chi Square Test for Goodness of Fit ? I have got a discrete data as given below (R script) ? No_of_Frauds<-c(1,1,1,1,1,1,1,1,1,2,1,1,1,1,1,1,2,1,2,2,2,1,1,2,1,1,1,1,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,5,1,2,1,1,1,1,1,1,1,3,2,1,1,1,2,1,1,2,1,1,1,1,1,2,1,3,1,2,1,2,14,2,1,1,38,3,3,2,44,1,4,1,4,1,2,2,1,3) ? I am trying to fit Poisson distribution to

Chi Square Test for Goodness of Fit   I have got a discrete data as given below (R script)   No_of_Frauds<-c(1,1,1,1,1,1,1,1,1,2,1,1,1,1,1,1,2,1,2,2,2,1,1,2,1,1,1,1,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,5,1,2,1,1,1,1,1,1,1,3,2,1,1,1,2,1,1,2,1,1,1,1,1,2,1,3,1,2,1,2,14,2,1,1,38,3,3,2,44,1,4,1,4,1,2,2,1,3)   I am trying to fit Poisson distribution to this data using R.  

Dear R-help, ? ? Chi Square Test for Goodness of Fit ? I have got a discrete data as given below (R script) ? No_of_Frauds<-c(1,1,1,1,1,1,1,1,1,2,1,1,1,1,1,1,2,1,2,2,2,1,1,2,1,1,1,1,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,5,1,2,1,1,1,1,1,1,1,3,2,1,1,1,2,1,1,2,1,1,1,1,1,2,1,3,1,2,1,2,14,2,1,1,38,3,3,2,44,1,4,1,4,1,2,2,1,3) ? I am trying to fit Poisson

Hello does anyone know how to set the confidence level within the seqMK() function in the pheno package. It seems to be set automatically at 0.05 and there seems to be neither an input function to set a different level, as there are with some changepoint functions, nor an output to give one the p-value of the changepoint identification which you get with functions ie func$p_value etc ... Thanks

[Moderator: This was erronously sent to R-announce, and filtered fortunately ] Hi, This is my first time to use R. I'm wondering which function I can use to do multiple comparison. I have an lm object and want to do multiple comparison based on this object. Splus has a function multicomp() but I could not find a similar one in R. Thanks in advance. Really appreciate it. Julie

Dear Thierry, thank you for the quick reply. I have only one question about the approach you proposed. As you suggested, imagine that the model we end up after the model selection procedure is: mod2.1 <- lmer(dT_purs ~ T + Z + (1 +T+Z| subject), data =x, REML= FALSE) According to the common procedures specified in many manuals and recent papers, if I want to compute the p_values relative to