similar to: Using 2SLS to mimic SEM with nested data

Hi, I am trying to obtain the heteroskedasticity consitent standard errors (HCSE) after apply 2SLS. I obtain 2SLS through tsls from package sem or systemfit: #### tsls #### library (sem) Reg2SLS <-tsls(LnP~Sc+Ag+Ag2+Var+R+D,~I2+Ag+Ag2+Var+R+D) summary (Reg2SLS) #### systemfit #### library (systemfit) RS <- LnP~Sc+Ag+Ag2+Var+R+D Inst <- ~I2+Ag+Ag2+Var+R+D labels

Dear all, I try to conduct a SEM / two stage least squares regression with the following equations: First: X ~ IV1 + IV2 * Y Second: Y ~ a + b X therein, IV1 and IV2 are the two instruments I would like to use. the structure I would like to maintain as the model is derived from economic theory. My problem here is that I have trouble solving the equations to get the reduced form so I can run

Hi, I am a bit confused on how code-words are derived from the codeword lengths. I will appreciate if someone can point me in the correct direction. I will take the example of an actual codebook that i found in a valid vorbis encoded file as shown below. [SK] +------Codebook [0] -------- [SK] Codebook Dimensions = 1 [SK] Codebook Entries = 8 [SK] Unordered [SK] 1, 6, 3, 7, 2, 5, 4, 7, [SK] NO

Hello, I am attempting to use smoothScatter to plot a heatmap of locations of events in an x-y axis. When I plot the heatmap without passing xlim and ylim parameters, it fills the plot area but the perspective is a bit skewed. I would like to standardize these plots to a uniform window size that does not depend on the range of values in the dataframe. However, when I resize the plot using xlim or

Hello This is a fun one for the list... Twice now, the Police have contacted us to say they have had a silent call then hangup from our landline number to the 999 service. As a matter of course, they follow up these calls in case someone is in distress. Nobody here was in distress - well, no more than normal! The Police aren't hugely happy when we tell them it must be a mistake. Thing

Hello- I am using R to build my initial models, but need to use AMOS to compare the models of two groups (adults vs. kids). The problem is I am getting different results with R and AMOS for the initial models of the separate groups (and the R results make more sense). The parameter estimates (path coefficients and variances) from both programs are nearly identical, but the model chi-squares

Hi List I want to carry out structural mode. Following Example l have taken from Basic Econometrics- Damodar Gujarati : Advertising intensity function: Ad/S = a0 + a1M + a2 (CD/S) + a3C + a4C2 + a5Gr + a6Dur – (1) Concentration function: C = b0 + b1 (Ad/S) + b2 (MES/S) -(2) Price-cost margin function: M = c0 + c1(K/S) + c2Gr + c3C + c4GD + c5(Ad/S) + c6 (MES/S)

Hi, i get factors from oracle instead real or numeric, but have problems to convert. Where is my mistake? I can't rember have this difficulties like this? many thanks, christian > vsub <- subset(dm,select=c(DEBITS_POST3)) > (vsub$DEBITS_POST3[1:4]) [1] 9,93 0 23,82 32,72 7936 Levels: 0 0,53 0,65 0,73 0,76 1,02 1,03 1,16 1,25 1,28 1,31 1,38 1,45 1,47 1,49 1,52 1,53 1,62 1,68

Hello, It has been found that SEM analysis using polychoric correlations + maximum likelihood estimator produces incorrect test statistics and standard errors (e.g., Flora, D. B., & Curran, P. J. (2004). An Empirical Evaluation of Alternative Methods of Estimation for Con?rmatory Factor Analysis With Ordinal Data. Psychological Methods, 9(4), 466-491). Standard errors can be dealt with by

I want estimate MIMIC latent variable with R in a Monte Carlo simulation. The packages plspm and semPLS don't permit to introduce MIMIC variable but only reflexives or formatives variables. The only one program which permits to use MIMIC latent variable with PLSPM seems to be XLSTAT, which can not be used to simulate a lot of data bases. It is a real challenge to develop a package with

I want to write a function mimic the function of select.list(), here is my preliminary version. select <- function(x,multiple=TRUE,...){ ans<-new.env() g <- gwindow(title=title,wid=200,heigh=500) x1<-ggroup(FALSE,con=g) x2<-gtable(x,multiple=multiple,con=x1,expand=TRUE) gbutton("OK",con=x1,handler=function(h,...){ value <- svalue(x2) if (length(value)==0)

Hi! Background: We have a normal NT 4.0 Domain called AIRPORT and a Windows 2000 Domain (server is in mixed mode) called MAIL. Connected to the AIRPORT Domain is a Samba 2.0.6 Server with security = domain. Both domains are trusting each other. I've a little problem understanding the user authentification with the trusted MAIL domain. I'll it explain with a little example: We have a

First I have to say I am sorry because I have not been so clear in my previous e-mails. I will try to explain clearer what it is my problem. I have the following model: lnP=Sc+Ag+Ag2+Var+R+D In this model the variable Sc is endogenous and the rest are all objective exogenous variables. I verified that Sc is endogenous through a standard Hausman test. To determine this I defined before a new

Dear Rologists, In order to combine plots I need to get access to the some "par"s specific to my plot prior to replot it with modified parameters. I have not found any option like "plot=F" associated with truehist and would like to know whether someone can point out how to overcome this problem. Thanks, Joh

> We should not mimic S here, sometimes. > I agree it's wrong in some places. > But if you use a different scheme, it should be > - well documented > - very consequently implemented ==> easily remembered by users One way to deal with improvements which force incompatabilities with S is to layer the code so that application programmers use a consistent

Dear all, Which data structure in R can mimic hash in PERL? I'd like to set up a lookup table, which could be accomplished by HASH if using PERL. Which of the data structures in R is the most efficient for lookup table? Thanks for your help. Best regards, Leon

I was trying to do what is on page 70 of John Chambers' new book namely using trace to invoke the browser by doing trace(zapsmall, edit = TRUE) but , typing above at an R prompt, I get trace(zapsmall, edit=TRUE) sh: EMACS: command not found Error in edit(name, file, title, editor) : problem with running editor EMACS I looked in the archives but maybe it's a problem with the

I would like to be able to use lme to fit random effect models In which some but not all of the random effects are constrained to be independent. It seems as thought the pdMat options in lme are a promising avenue. However, none of the existing pdMat classes seem to allow what I want. As a specific example, I would like to fit a random intercept/slope mixed model to longitudinal observations in

Dear members, I would like to switch from nlme to lme4 and try to translate some of my models that worked fine with lme. I have problems with the pdMat classes. Below a toy dataset with a fixed effect F and a random effect R. I gave also 2 similar lme models. The one containing pdLogChol (lme1) is easy to translate (as it is an explicit notation of the default model) The more parsimonious

Dear all Seems that puzzles always come in packs. I was asked to help with some statistics in blood analysis. (You can not refuse your wife's asks :-). She has contingency table for values IgVH mutation and ZAP expression. I can do chi-square test (in R) and get a results, and with some literature I can try explain them. However she found an article in which they use SPSS and use