similar to: how to get coefficients of regression or Anova

Howdy I apologize for duplicated posting. But I decided to correct my previous posting. I had the regression results using r <- lm(Y ~ nemp + as.factor(devt), data=d). First, there is the result of anova(r). Here I could not find regression coefficients. Response: Y Df Sum Sq Mean Sq F value Pr(>F) nemp 1 58.2 58.2 1233.23 < 2e-16 ***

Howdy Gurus ! I have a different correlation result from the same data. The "corridor1" string variable is expressed as a number like the "corridor2" number variable. -------------------------------------------------------------------------- > levels(corridor1) [1] "A" "B" "C" "D" "E" "F" >

----------------------------------------------------------------------------------------------------- Howdy, Gurus I am appying R package for regression analysis as followings. A dependent variable is jhnet that means ratio of dividing internal trip with all trips in a traffic zone. There are many indepentent variables including factor or dummy varibles such as parkfee, ohouse, Devt2, corridor1.

would someone be kind enough to paste the code below into an R session ( ir you can paste it into a file and just source it ) and take a look at it ? I must be doing something wrong but i can't find it. I start out with a zoo object that has 100 elements in it. then, i only want to keep the rows in which the bid and the ask are both grester than zero. ( maybe my logic is wrong there ? ).

Hallo, I have this dataset with repeated measures. There are two within-subject factors, "formant" (2 levels: 1 and 2) and "f2 Ref" (25 levels: 670, 729, 788, 846, 905, 1080, 1100, 1120, 1140, 1170, 1480, 1470, 1450, 1440, 1430, 1890, 1840, 1790, 1740, 1690, 2290, 2210, 2120, 2040, 1950), and one between-subject factor, lang (2 levels:1 and 2). The response variable

To anyone who can help: I have two brief questions concerning sapply. Following below is the code for my example. The two problems are described at the end of the code: site <- rep(2:6, each = 12) tillage <- rep(c(1,-1), each = 6, times = 5) carbon <- c(18.23, 16.06, 17.81, 16.07, 17.26, 17.08, 14.92, 15.88, 12.11, 14.23, 16.99, 13.57, 20.34, 20.3,

Hello everybody, I'm running a panel regression with dummy variables controlling for years. While this works fine for most of my models, in some cases I get the error message "In sqrt(diag(object$vcov)) : NaNs wurden erzeugt" and missing results for some or all of my year dummies: Estimate Std. Error z-value Pr(>|z|) year2000

The pretty picture that I saw at: http://chartsgraphs.wordpress.com/2009/02/09/r-panel-chart-beats-excel-chart/#more-1096 inspired me to try something similar. The code that I wrote is: ------snipsnip--------------------------------------------------------------------- M <- structure(list(date = structure(c(13634, 13665, 13695, 13726, 13757, 13787, 13818, 13848, 13879, 13910, 13939, 13970,

Hi, my data consists of 2 columns: one with the 'year' when daily observation was recorded, the other one consists these observations 'obs', like the following: year obs [3014,] 86 26.01 [3015,] 86 25.66 [3016,] 86 23.92 [3017,] 86 23.84 . . [3018,] 96 22.65 [3019,] 96 23.22 [3020,] 96 23.36 . . [3021,] 97 24.55 [3022,] 97 27.63 [3023,] 97 27.92 [3024,] 97

Hi I have been trying so many different things to get my Inverse Mills Ratio going for a Two stage Heckman Model, I have tried the following so far (the commands are listed below till teh point where I get an error), I get an error in the last sentence (marked in bold below), if this were successful then I could have used the IMR as a control in my OLS (which would be the OLS for the outcome

Am I trying to perform multiple linear regressions on each 'VARIABLE2'. I figured out that there are different ways, using the following code: (data is given at the end of this message) reg <- lapply(split(TRY, VARIABLE2), function(X){lm(X2 ~ X3, data=X)}) lapply(reg, summary) Which produces the following: $`1` Call: lm(formula = X2 ~ X3, data = X) Residuals: Min

I am struggling to generate p values for comparisons of levels (post-hoc tests) in a glm with a negative binomial distribution I am trying to compare cell counts on different days as grown on different media (e.g. types of cryogel) so I have 2 explanatory variables (Day and Cryogel), which are both factors, and an over-dispersed count variable (number of cells) as the response. I know that both

Hi R Users, I created interaction plots in ggplot2 and was trying to add output of two way ANOVA models, especially only interaction ( example treatment*control F(XX, XX) = xxx, p = xxx) into figures, but i was not able to add. Would you mind to help on how I can add information into each figure? I have attached the example data and the code that I used for this. dat<-structure(list(Sites

Dear all: I converted the columns (Baci, Meti, Fungii, Protozoai) into integers (using excel) and then imported the data (.txt) into R. Interestingly, the other three variables were loaded as INT, but the 'Baci' one continued as Num. I imported the data using the following command line: X <- read.delim(file.choose(), header = TRUE, dec =

I am a novice R user, and I am having difficulty understanding R's influence plots. I am trying to remove outliers from a particular variable, "sib." I am able to generate influence plots and further outlier information such as below (which is a shortened example). For my analyses, I end up excluding the points R refers to, 7, 18, 26, and 105. However, my question is, how can I

Hi, I fit a Cox PH model to estimate the cause-specific hazards (in a competing risks setting). Then , I compute the survival estimates for all the individuals in my data set using the `survfit' function. I am currently playing with a data set that has about 6000 observations and 12 covariates. I am finding that the survfit function is very slow. Here is a simple simulation example

Hi, Can anybody tell me what the message below means and how to overcome it. Thanks, Neil Warning message: X matrix deemed to be singular; variable 2 in: coxph(Surv(age_at_death, death) ~ project$pluralgp + project$yrborn + ......... >

Attached are the Polyhedron 2005 benchmark results for current llvm/dragonegg svn on x86_64-apple-darwin11 built against Xcode 4.3.2 and FSF gcc 4.6.3. The benchmarks for -msse3 and -msse4 appear identical (at least for degg+optnz). This is fortunate since there seems to be a bug in -msse4 on 2.33 GHz (T7600) Intel Core 2 Duo Merom (http://llvm.org/bugs/show_bug.cgi?id=12434). I've added two

I have been using Samba 4 kerberos and ldap with dovecot. Samba 4 changed a while back (resulting in me asking for help) which requires kerberos auth for ldap lookups. My setup worked perfectly before hand. Before and after were with dovecot-2.0.11 and the after also happens with 2.0.11. The only changes were (in my ldap.conf for dovecot -- changes are new lines starting with *, * is not in the

library(StreamMetabolism) day <- (structure(c(10.08, 10.08, 10.05, 10.03, 10, 9.98, 9.96, 9.95, 9.95, 9.96, 9.96, 9.98, 10.01, 10.05, 10.06, 10.09, 10.11, 10.11, 10.13, 10.13, 10.15, 10.15, 10.13, 10.14, 10.11, 10.13, 10.14, 10.13, 10.12, 10.13, 10.14, 10.16, 10.18, 10.19, 10.23, 10.27, 10.33, 10.37, 10.45, 10.57, 10.6, 10.66, 10.73, 10.77, 10.84, 10.86, 10.87, 10.94, 10.98, 11.01, 11.05,