search for: twoways

I've tried without success to calculate interaction and main effects contrasts using R. I've found the functions C(), contrasts(), se.contrasts() and fit.contrasts() in package gmodels. Given the url for a small dataset and the two-way anova model below, I'd like to reproduce the results from appended SAS code. Thanks. --Dale. ## the dataset (from Montgomery) twoway <-

Hello Giovanni I made a minor modification to your function, which now allows to compute the within R-sq in Twoways Within models (see below). However I ran into an issue that I have already encountered before: whenever I try to fit Twoways Within models on my unbalanced data, the process is strangely slow and I usually terminate it either after ~15min or when my CPU hits 100C. This is similar to what I mention...

Hello everyone, I have a peoblem to create the twoways effect in the plm package. when i try to create the following dsn1<-plm(lnQ~lnC+lnL+lnM+lnE+eco+RD,data=newdata,effect="twoways",model="within") i have this error: Error in rep.int(c(1, numeric(n)), n - 1L) : negative length vectors are not allowed and to be honest i...

Dear R users What would be the best way to approach estimating a panel regression with twoways random effects, on unbalanced data? Unfortunately, the "plm" package has no implementation of twoways random effects for unbalanced data. Currently I'm considering two approaches: - extend "plm" to cover this type of panel regression. (For the authors, cc'ed:) Would impl...

Dear R users I get different F-statistic results for a "within" model, when using "time" or "twoways" effects in plm() [1] and when manually specifying the time control dummies [2]. [1] vignette("plm") [2] http://cran.r-project.org/doc/contrib/Farnsworth-EconometricsInR.pdf Two examples below: library("AER") data("Grunfeld", package = "AER") library(&q...

Hi all, I've been running loglinear models for three-way tables: one of the variables having three levels, and the other two having two levels each. An example looks like below: > yes.no <- c("Yes","No") > switch <- c("On","Off") > att <- c("BB","AA","CC") > L <- gl(2,1,12,yes.no) > T <-

I am using it on a big dataset. The estimation was done in hours. But summary() takes forever. Any suggestion is greatly appreciated! [[alternative HTML version deleted]]

Hi, all There are 62 samples in my data and I tested 3 times for each one, then I want to use ICC(intraclass correlation) from irr package to test the consistency among the tests. *combatexpdata_p[1:62] is the first text results and combatexpdata_p[63:124] * is the second one and *combatexpdata_p[125:186]* is the third. Here is the result:

Hi, I am trying to estimate a two-way model with both individual and time fixed effects. I am using plm with "twoways" specification. plm(as.integer(yvar) ~ xvar, index = c("id", "time"), model="within", data=dataset, effect = "twoways") But I get keep getting the following message and I don't know what to do about it, because I don't think anything is wrong w...

Hi... In Stata, there is the ability to display scatter plots with data points at the same (x,y) location, using the 'jitter' command of the twoway scatter stata command. Anyone know of a way that I can do the equivalent thing in R? For non-Stata readers, if jitter is enabled in stata, and n-points would be at the same (x,y) location, the points are offset a bit (according to

Hello to all on the list, I'm trying to estimate a fixed effects model from a large (unbalanced) panel data set. I have no problems when using only an individual effect or only a time effect, but I get an error message when I try for a "twoways" effect. Here is some of the code: paneldata27 is the entire panel data set: > dim(paneldata27) [1] 1178831 8 > paneldata27<-plm.data(paneldata27,index=c("Account","Day.of.Sample")) > nlevels(paneldata27$Account) [1] 1573 > nlevels(paneldata27$Day.of....

I've been searching for an answer to this for a while but no joy. I have a simple 2-way ANOVA with an interaction. I'd like to determine the power of this test for each factor (factor A, factor B, and the A*B interaction). How can I do this in R? I used to do this with "proc Glmpower" in SAS, but I can find no analogue in R. [[alternative HTML version deleted]]

...y_t<-pmodel.response(plm(formula=inv~value,data=Grunfeld,index=c("firm","year"),model="within",effect="time")) dem_y_it<-pmodel.response(plm(formula=inv~value,data=Grunfeld,index=c("firm","year"),model="within",effect="twoways")) dem_X_it<-model.matrix(plm(formula=inv~value,data=Grunfeld,index=c("firm","year"),model="within",effect="twoways")) sum(y_i!=dem_y_i) #y_i[1:10] #dem_y_i[1:10] sum(y_t!=dem_y_t) #y_t[1:10] #dem_y_t[1:10] sum(y_it!=dem_y_it) #y_it[1:10] #dem_y_it...

Hi R Users, I have a dataframe like this: id x rho A 1 0.1 B 20 0.5 C 2 0.9 ... I want to do a scatter plot of "x" versus "rho" but for each point on the scatter plot I want the corresponding entry for "id" instead of points. In STATA I can do so by twoway (scatter x rho, mlabel(id)) How can I do the same in R? I am sure there is some simple way to do

Hello, I want to know if there are some functions or packages to solve differential and integral equation using R. Thanks. Shao chunxuan. [[alternative HTML version deleted]]

Hi, In SPlus there is a function called "twoway" for median polishing gridded data. Is there an equivalent function in R? I have been searching for it in R help without much success. Your help is much appreciated. Cheers Sorn [[alternative HTML version deleted]]

Hi, I have two different imaging modalities (for the identification of areas of infarcted myocardium) that I need to compare regarding agreement and consistency. However, I don't think that methods like Cohen's Kappa, PCC, Bland-Altmann or ICC are sufficient here as there is not just a pairwise but also a spatial relationship between measured data points. For example if the results of the

Hi, I am trying to estimate a two-way model with both individual and time fixed effects. I am using plm with "twoways" specification. plm(as.integer(yvar) ~ xvar, index = c("id", "time"), model="within", data=dataset, effect = "twoways") But I get keep getting the following message and I don't know what to do about it, because I don't think anything is wrong w...

...n producing a &lt;summary(model.object). The code I am using is: &gt; b<-plm.data(b,index=c("E","M")) > b.fetw<-plm(B~lag(B,k=1)+Ma+lag(Ma,k=1)+Pa+lag(Pa,k=1)+Ya+lag(Ya,k=1)+F+lag(F,k=1)+CS+R+lag(R,k=1)+G+I, > data=b, model="within", effect="twoways") > summary(b.fetw) Twoways effects Within Model Call: plm(formula = B ~ lag(B, k = 1) + Ma + lag(Ma, k = 1) + Pa + lag(Pa, k = 1) + Ya + lag(Ya, k = 1) + F + lag(F, k = 1) + CS + R + lag(R, k = 1) + G + I, data = b, effect = "twoways", model = "within"...

Here are the functions documented in the Blue Book that I found missing in R (ignoring the ones which are obviously outdated). aggregate allocated amatch axes chull clorder cutree cycle date debugger dget discr faces interp l1fit labclust lag loglin monthplot mstree mulbar napsack odometer persp plclust plotfit rep.int restore rreg sabl sablplot set.seed smooth sort.list Stable stars