similar to: RE: OT (a little): IPV6 Ramifications Article

We have the ability to create random UID's on own system through a custom CGI API. These UID's are written to individual sip configuration files based on the account name, so for instance sip_TEST.conf, sip_TEST2.conf, and sip_TEST3.conf, etc. Many of these UID's are created on the fly and at random times throughout the day. Right now, I have it setup to do a reload every night.

I am currently looking at putting together an Asterisk PBX system for my home office. One of the things I need is an expandable 2-line corded/cordless phone system. If I wasn't using Asterisk, I'd be getting one of these AT&T systems with 2 extra handsets. http://telephones.att.com/attui/shop/product_detail.cfm?itemID=ad53fe08-495e-41b6-b390-3aaa1c84cc40 So, the question is,

Dear all, I was wondering whether anyone knows about a program which converts (part of) a data definition file (such as a .dct file for stata, or .sas file for sas) into an R-script. Here is an example with a .sas file: <-- snipp VALUE HTYPE (default=32) 0 = "Not in household" 1 = "Married couple family household" 2 =

Dear all, sorry, this is for sure really basic, but I searched a lot in the internet, and just couldn't find a solution. The problem is to create new variables from a data frame which contains both individual and group variables, such as mean age for an household. My data frame: df hhid h.age 1 10010020 23 2 10010020 23 3 10010126 42 4 10010126 60 5 10010142

Dear R users, I am trying to convert a dataset from one format to several rectangular datasets. A consultant helped design the data entry program for our survey using Delphi/Pascal and for each household the information is stored in a file called "EA-HM-HH.TXT" where EA is the enumeration area number, HM is the homestead number and HH is the household number. Within this file the

Hi R-users!! I have some trouble with the survey pakage and i would be very glad if you can give me an advice. I have a sample from a survey where household were interviewed. The sample has 4 criteria on which the stratification was based: REGION, SIZE OF HOUSEHOLD, SIZE OF LOCALITY, AGE OF HEAD OF HOUSEHOLD. Since i don't have the whole information in each cell of the cross

Dear All, I'm analysing a negative binomial dataset from a population-based study. Many covariates were determined on household level, so all members of a household have the same value for those covariates. In STATA, there seems to be an option for 'clustered analysis' for neg-bin regression. Does an equivalent exist for R(MASS)'s glm.nb or a comparable function? Many thanks for

Hello, I need some help in creating a new variable. I need to create a 'couple identifier', which gives a unique code for every couple/triple/... in a household. So, I can identify couples. To do this, I should use 4 variables: * SERIAL = a unique numeric code for each household * PERNUM = a unique numeric code for each person * SPLOC = the numeric code of the spouse in the

Hi all, I have a dataset of individuals where the variable ID corresponds to the identification of the household where the individual lives. rel.head stands for the relationship with the household head. so rel.head=1 is the household head, rel.head=2 is the spouse, rel.head=3 is the children. Here is an example to see how it looks like: df<-data.frame(ID=c("17100",

I have a people table with four types of people: clients, spouses, children, and others all setup using single-table inheritance with a foreign key back to a household record. A Household has_one client and spouse, and has_many children and others. I want to use a single "Household.find(@session [:household_id], :include => [:client, :spouse, :children, :others])"

I've written a function that takes some input data output from a simulation model and creates some graphs. It's not very complicated code, and it works perfectly fine if I just run the code as is. But I have converted it into a function so we call it externally, and when I try to source the code to test the function, I get the error message "variable names are limited to 256

Dear R-users, Recently I had to analyze a dataset from household survey. The sample design ensured, that each household in the population has the same probability of being sampled. However the data were gathered from only one adult individual in each household, who was randomly choosen by an interviewer (via "Kish grid"). To equalize the probabilities for each INDIVIDUAL a casewise

I would appreciate help in knowing how to repeat categorical variable code given in column=A, by the number in a matching column=B. For example, I have a categorical variable code attributed to a household=A and want to replicate the code for all member of the household, as given in column=B. I would like to have one sequence of categorical variable codes for individuals in column C. I have ~9000

Good afternoon! As mentioned in the subject, my question regards more the methodological part that accompanies survey design and the statistical part that is involved. So, I have the following data: a<-data.frame (id_hh=c(1:5), strata=c(1,1,2,2,1), Nhstrata=c(100,100,200,200,100), Nrmemb=c(2,4,2,5,4)) a$ocmemb1<-c("wk","jl","st","jl","st")

Hi, I am trying to run a logistic regression to look at the risk of malaria infection in individuals. I want to account for intra household correlation and so want to include a household level random effect. I have been using the lmer command in lme4 package but am getting some strange results that are completely different to those I get using STATA. Can I just check that this is the correct

I have the following sample dataset (CSV input here:http://goo.gl/YR8LP. CSV output here: http://goo.gl/EFCC8) which I want to transform as follows. For each person in a household I want to create two new variables OrigTAZ and DestTAZ. It should take the value in TripendTAZ and put that in DestTAZ. For OrigTAZ it should put value of TripendTAZ from the previous row. For the first trip of every

Hi all, For various reasons I need to have foreign keys with not null constraints. Eg: create_table :people do |t| t.column :name, :string t.column :household_id, :integer, :null => false end create_table :households do |t| t.column :name, :string end add_foreign_key_constraint :people, :household_id, :households, :id So the people table has a foreign key into

Estimados usuarios: Estoy intentando reproducir el ejemplo 6.4 de Thomas Lumley. Complex Survey. Editorial Wiley. 2010 (ver la página en google:

Hi All, I am working on an example where the electric utility is investigating the effect of size of household and the type of air conditioning on electricity consumption. I fit a multiple linear regression Electricity consumption=size of the house hold + air conditioning type There are 3 air conditioning types so I modeled them as a dummy variable Type A Type B Type C Where type A is the

Dear All, I am doing a growth modeling using NLME. I have three levels in my data: observation, individual, household. About half of my total sample have missing values in my household-level covariates. Under this situation, the best way to go is probably to multiply impute the data (for, say, 5 times), estimate the same model separately on each model using LME function, and merge the results. My