search for: bollen

Hi! I want to construct a path analysis model that can account for measurement error in totally aggregated parcels, which refer to parcels where all of the items in a scale are summed or averaged. If I am not mistaken, Bollen (1989) advocates the following formula for computing the error variance of each parcel: (1−α(parcel))×variance(parcel), such that α refers to Cronbach's alpha, which is a measure of reliability. What follows is the following path analysis model in theory (i.e., in practice the formulas are r...

Hi, Is it possible to create new vars in a loop For instance: for (i in 1:11) var'i' <- assign something output = var1 var2 ... var11 Is there a way to combine/join the value of 'i' to the string/char var in de loop. -- View this message in context: http://www.nabble.com/join-chars-in-loops-tp16895854p16895854.html Sent from the R help mailing list archive at

Hi, I have a dataframe wf existing of a header with different labels and beneath the values of those labels : wf: label1 label2 ... 0,45 0,21 0,10 0,45 .... .... I have a list fl <- c("label2","label3",..) Isn't possible to use the list elements in the list in order to subtract values from the dataframe? like : wf$fl[[1]] When I do in R I get :NULL

...* (log(det(E)) - log(det(O)) + sum(diag((O %*% solve(E))))-p) N=size of group p=number of variables E=expected covariance matrix O=observed covariance matrix where in your example, E will be the observed covariance matrix for the pooled groups. There are GLS etc alternatives - see eg Bollen's book on SEM. | David Duffy (MBBS PhD) ,-_|\ | email: davidD at qimr.edu.au ph: INT+61+7+3362-0217 fax: -0101 / * | Epidemiology Unit, Queensland Institute of Medical Research \_,-._/ | 300 Herston Rd, Brisbane, Queensland 4029, Australia GPG...

...ing standardized solutions, fit measures, modification indices and more To get a first impression of how the 'lavaan model syntax' looks like, below is the full R code for fitting a SEM model: ## begin R Code ## library(lavaan) # The industrialization and Political Democracy Example # Bollen (1989), page 332 model <- ' # latent variable definitions ind60 =~ x1 + x2 + x3 dem60 =~ y1 + y2 + y3 + y4 dem65 =~ y5 + y6 + y7 + y8 # regressions dem60 ~ ind60 dem65 ~ ind60 + dem60 # residual correlations y1 ~~ y5 y2 ~~ y4 + y6 y3 ~~...

...modeling. More information can be found on the website: http://lavaan.org To get a first impression of how the 'lavaan model syntax' looks like, below is the full R code for fitting a SEM model: ## begin R Code ## library(lavaan) # The industrialization and Political Democracy Example # Bollen (1989), page 332 model <- ' # latent variable definitions ind60 =~ x1 + x2 + x3 dem60 =~ y1 + y2 + y3 + y4 dem65 =~ y5 + y6 + y7 + y8 # regressions dem60 ~ ind60 dem65 ~ ind60 + dem60 # residual correlations y1 ~~ y5 y2 ~~ y4 + y6...

...that apply bootstrapping to SEM models? I'm guessing that's a fairly straightforward application of existing functions, but would rather not reinvent the wheel. Coefficient p-values should be straightforward, but I'm not sure what it would take to get bootstrapped indicators like the Bollen-Stine p-value. Peter

Hi, I have the following data imported from a csv file user_id site_id name 1 1 11 februari 2 1 11 redbook 3 1 11 tips 7 3 6 sleep 8 3 6 monitoring 9 3 6 alarm Which I would like to merge/combine into user_id site_id name 1 1 11 februari,

...ighly interconnected node. When I went through nabble R Archive and I found many message but I do not think there was any message in regard to this. I did find one Article by I have attached in this mail. Co-authorship networks in the digital library research community Xiaoming Liu ,*, Johan Bollen , Michael L. Nelson , Herbert Van de Sompel They have done exactly what I am looking for.They have done bottom up hierarchical Clustering. Is there anyway I can do this in R. Help on this would be great. Thanks a lot Nathan http://www.nabble.com/file/p22358708/Clustering%2BTechnique.pdf Clust...

Hi, I would like to iterate over a dataframe and plot several graphs over several pages. For instance, an iteration over the dataframe will result in 20 plots. Since 20 plots in one page is too much (too many small plots) I would like to distribute them over 5 pages with each 4 plots. I know how to create multiple plots on one page with : par(mfrow=c(2,2)) -- View this message in context:

...ing standardized solutions, fit measures, modification indices and more To get a first impression of how the 'lavaan model syntax' looks like, below is the full R code for fitting a SEM model: ## begin R Code ## library(lavaan) # The industrialization and Political Democracy Example # Bollen (1989), page 332 model <- ' # latent variable definitions ind60 =~ x1 + x2 + x3 dem60 =~ y1 + y2 + y3 + y4 dem65 =~ y5 + y6 + y7 + y8 # regressions dem60 ~ ind60 dem65 ~ ind60 + dem60 # residual correlations y1 ~~ y5 y2 ~~ y4 + y6 y3 ~~...

...modeling. More information can be found on the website: http://lavaan.org To get a first impression of how the 'lavaan model syntax' looks like, below is the full R code for fitting a SEM model: ## begin R Code ## library(lavaan) # The industrialization and Political Democracy Example # Bollen (1989), page 332 model <- ' # latent variable definitions ind60 =~ x1 + x2 + x3 dem60 =~ y1 + y2 + y3 + y4 dem65 =~ y5 + y6 + y7 + y8 # regressions dem60 ~ ind60 dem65 ~ ind60 + dem60 # residual correlations y1 ~~ y5 y2 ~~ y4 + y6...

...????????? 56 ? 0????????????????????? ???????????????????????????41 ? Estimator???????????????????????????????????????? ML ? Minimum Function Chi-square??????????????????? 6.171 ? Degrees of freedom???????????????????????????????? 6 ? P-value??????????????????????????????????????? 0.404 ? P-value (Bollen-Stine Bootstrap)?????????????? 0.566 Chi-square for each group: ? 1????????????????????????????????????????????? 4.832 ? 0????????????????????????????????????????????? 1.339 Parameter estimates: ? Information?????????????????????????????? ??Observed ? Standard Errors??????????????????????????? Boo...

Hello. I have been browsing the R- manual and not seen any direct implementation of Factor analysis. Is there anyone out there who has run Factor Analysis with R? Thanks Michael -- Michael Preminger Forsker / Research Scientist Avdeling for journalistikk, bibliotek- og informasjonsfag / Faculty of Journalism, Library and Information Science H?gskolen i Oslo / Oslo College

Dear R People: Could someone recommend a "baby book" on path analysis and SEM, please? Or if someone has an example that they use in the classroom setting, that would be very cool too. Thanks in advance, Sincerely, Erin -- Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: erinm.hodgess at gmail.com

Hi, I have loaded a dataset in R : data = label freq1 freq2 news 54 35 fun 37 21 milk 19 7 food 3 3 .... etc And I have a vector flist<-c("fun","food") Now I want to use the vector 'flist' for selecting these values from 'data' so that I get the following dataset : label freq1 freq2 fun 37 21 food

...ation indices and more > > To get a first impression of how the 'lavaan model syntax' looks like, > below is the full R code for fitting a SEM model: > > ## begin R Code ## > > library(lavaan) > > # The industrialization and Political Democracy Example > # Bollen (1989), page 332 > > model <- ' > # latent variable definitions > ind60 =~ x1 + x2 + x3 > dem60 =~ y1 + y2 + y3 + y4 > dem65 =~ y5 + y6 + y7 + y8 > > # regressions > dem60 ~ ind60 > dem65 ~ ind60 + dem60 > > # residual corre...

Yesterday I was forced to migrate servers due to a hardware failure. I have been able to bring up my mail server, and set up Squirrelmail and Dovecot. I am able to access (via Squirrelmail) all users' mail except one - which happens to be my wife's, so it would be really helpful if I could get that working too. I am able to log in, but see the following message in the main pane:

1. Martin Maechler's comments should be taken as replacements for anything I wrote where appropriate. Any apparent conflict is a result of his superior knowledge. 2. 'eigen' returns the eigenvalue decomposition assuming the matrix is symmetric, ignoring anything in m[upper.tri(m)]. 3. The basic idea behind both posdefify and nearPD is to compute the

Someone can help me? I tried several things and always don't converge # Model library(sem) dados40.cov <- cov(dados40,method="spearman") model.dados40 <- specify.model() F1 -> Item11, lam11, NA F1 -> Item31, lam31, NA F1 -> Item36, lam36, NA F1 -> Item54, lam54, NA F1 -> Item63, lam63, NA F1 -> Item65, lam55, NA F1 -> Item67, lam67, NA F1 ->