similar to: Proc Nnpar1way with D option - equivalent in R

Can R support data manipulation programming that is available in the SAS datastep?  Specifically, can R support the following: -          Read multiple dataset one record at a time and compare values from each; then base on if-then logic write to multiple output files -          Load a lookup table and then process a different file; based on if-then logic, access and lookup values in the table

In response to those who asked for a better explanation of what the Vilno software does, here's a simple example that gives some idea of what it does. LABRESULTS is a dataset with multiple rows per patient , with lab sodium measurements. It has columns: PATIENT_ID, VISIT_NUM, and SODIUM. DEMO is a dataset with one row per patient, with demographic data. It has columns: PATIENT_ID, GENDER.

I have over 300 variables in my table. I want to choose only a handful of those variables to run through many procedures. Lm(), glm() etc..i have over 10 procedures that i need to run those variables everytime. Those handful of variables can change everytime if output is satisfactory or not. I have done this in SAS. Now i need to know how to do this in R. Any help or even if someone can point to

As noted on the R-project web site itself ( www.r-project.org -> Manuals -> R Data Import/Export ), it can be cumbersome to prepare messy and dirty data for analysis with the R tool itself. I've also seen at least one S programming book (one of the yellow Springer ones) that says, more briefly, the same thing. The R Data Import/Export page recommends examples using SAS, Perl, Python, and

In clinical trial data preparation and many other data situations, the statistical programmer needs to merge and re-merge multiple input files countless times. A syntax for merging files that is clear and concise is very important for the statistical programmer's productivity. Here is how Vilno does it: inlist dataset1 dataset2 dataset3 ; joinby variable1 variable2 where ( var3<=var4 ) ;

Hello Everyone,   Below is some SAS code that uses a "line hold specifier" to read multiple observations from each of several input lines of data. There are 3 patients per line in the in-stream data.   Is there a way in R to read this kind of data? I've looked in my books and online but haven't found anything   Thanks,   Paul     DATA EXAMP.TRIAL; INPUT TRT $ CENTER PAT SEX $ AGE

To account for likely differences between families in naturalization rates, we fitted a generalized linear mixed model, using PROC NLMIXED in SAS10, with the naturalization rate per genus (that is, the number of naturalized species in a genus as a proportion of the total number of introduced species in a genus) as the response variable, a variable coding genera as containing at least one native

Example: I have the following model > model <- lmer(response ~ time * trt * bio + (time|id), data = dat) where time = time of observation trt = treatment group (0-no treatment / 1-treated) bio = biological factor (0-absent / 1-present) and I would like to obtain an estimate (with standard error) of the change in response over time for individuals in the

Dear R-users, I am looking for a R function that would be the equivalent of the SAS proc freq ( http://support.sas.com/documentation/cdl/en/procstat/63104/HTML/default/viewer.htm#/documentation/cdl/en/procstat/63104/HTML/default/procstat_freq_sect006.htm). The table, ftable, xtabs functions are close but do not quite offer the same capabilities (e.g. they just return counts and no %ages as far as

Hello All, Here is the requested information. Most of it was on the original post for the "Tools For Preparing Data For Analysis" thread from last week, but it got overlooked. They are all given under an open source license. Check 'em out! ******************************************************* Vilno: data transformation software, that reads in input datasets (rows and columns),

Dear R users, Biostatistics Denmark would like to annouce the availability of the new utility: sas2R --- a SAS to R parser. For almost 40 years SAS has been the primary tool for statisticians worldwide and its easy-to-learn syntax, unsurpassed graphical system, powerful macro language and recent graphical user interfaces have made SAS the number one statistical software choice for both beginners

Hi useRs, I have a set of fortran code that was passed down from previous students, and I am converting its algorithm into R codes. I encounter this function in Fortran (D)QDAWO, which numerically integrates a function f with a user-specified cosine or sine weight. It is used because the original function that I want to integrate is f(x)*cos(x). I tried in R to directly integrate by

Dear List What is the R package equivalent of Proc Varclus or Information Value. ANy assistance in determining R equivalents of f Oblique Component Analysis (PROC VARCLUS), Information Value (IV) and Weight Of Evidence (WOE) analysis, and business intelligence http://www.nesug.org/proceedings/nesug06/an/da23.pdf Regards, Ajay Websites- http://decisionstats.com [[alternative HTML version

On 8/10/2017 8:34 AM, Dennis F. Kahlbaum wrote: > -- snip -- I don't have real help, but I'll remind you that R is case sensitive, and it looks like that will be at least one problem in the solution your are working on below: lme not LME data not DATA random = RANDOM > ------------------------------------------------------------------ > > The R code I've devised for the

> On Aug 11, 2017, at 7:56 AM, Dennis F. Kahlbaum <kbomb at umich.edu> wrote: > > Hi Robert: > > Thanks for your response, as well. > > I'm sorry. As you've discovered, I made some capitalization errors when posting my R code. The actual R code does use "lme", "data", and "random". > > The dataframe is indeed named

Dear Dennis, Your question assumes that people know both SAS PROC MIXED and R nlme. Only a limited number of people do. Add the mathematical formulation of the model. That will increase the number of people that can help you. Adding the number of levels in each categorical variable and the number of observation per group is useful too. Best regards, ir. Thierry Onkelinx Instituut voor natuur-

Hi Robert: Thanks for your response, as well. I'm sorry. As you've discovered, I made some capitalization errors when posting my R code. The actual R code does use "lme", "data", and "random". The dataframe is indeed named "emiss" and each item in the formula is a column in the dataframe. I used the following R code to read in the

Dear All, I am trying to calculate a 95% confidence interval for the difference in two c statistics (or equivalently D statistics). In Stata I gather that this can be done using the lincom command. Is there anything similar in R? As you can see below I have two datasets (that are actually two independent subsets of the same data) and the respective c statistics for the variables in both cases.

RoR Equivalence of TSQL Stored Procedures and User defined functions As I browsed through the tutorials and online eBook ?Programming Ruby?, I have not come across the terms ?Stored Procedures? or ?User-defined functions? as I know them in SQL 2000. However, the online documentations in MySQL 5.0 show that Stored Procedures and User-defined functions are supported in MySQL 5.0. I wonder what

I am trying to reproduce some old SAS PROC MIXED code using R and nlme. The data consists of emission readings from vehicles and fuel properties. All variables are real numbers except "study" and "vehicle", which are character. Unfortunately, since the data are confidential, I'm unable to provide an example. The original SAS v6.12 code is provided below: