spss

I have two versions of SPSS at work. SPSS 11 running on Windows XP and SPSS 20 running on Linux. Both copies of SPSS work fine. Files created with either version of SPSS open without incident on the other version of SPSS. I.E. - I can create a .sav file with SPSS 20 on Linux and open it on SPSS 11 on Windows without incident. But, if I create a .sav file with SPSS 20 and import the data into either R or PSPP (on Linux), I get a bunch of warnings. The data appears to import correctly, but I am concerned by the warnings. I do not see any warning when importing a .sav from SPSS 11 or other .sav

I need to export some data and then I have to export them in a SPSS file format. I've already found out that I need a SPSS SDK. I also have found out that i need a I/O DLL for creating and reading these files. But I cannot find them. Can anybody please send me the direct link, as it seems that I'm too dumb to find it. Please help! Thanks in advance PS: I just need to create some SPPS files and I don't have any SPSS licence. EDIT: it'a an webapplication on the internet, and the client wants us to generate SPSS files, so he can download it make some statistics You can get the SPSS I/O materials

I have this monster query written in T-SQL that pulls together and crunches data from multiple tables. I can export the result to CSV or Excel easily enough, but would like to send it right into SPSS. The ODBC drivers in SPSS only recognize Tables and Views in my SQL database. Any ideas how to get the results of my query into SPSS? Options: Export to Excel then import to SPSS... formatting things like dates become unwieldy Save query as a table in my database... but then I would have to make a new table every time I run the query, yes? As recommended below, simply run my SQL statement in the

I have mongodb where my data is stored. I am using SPSS where I have do some data analysis. Can someone help me in connecting SPSS to mongodb. Thank you. Are you using SPSS Modeler or Statistics? In both cases you can access MongoDB using R. Both Statistics and Modeler have integration with R. So you can just use the R package 'rmongodb' and connect to your MongoDB. Here you have some links: https://docs.compose.io/languages/r.html http://www.r-bloggers.com/r-and-mongodb/ Remember to use R with Statistics you need to install the plugin 'IBM SPSS Statistics - Essentials for R' ftp://public.dhe

As usual, I got some SPSS file that I've imported into R with spss.get function from Hmisc package. I'm bothered with labelled class that Hmisc::spss.get adds to all variables in data.frame , hence want to remove it. labelled class gives me headaches when I try to run ggplot or even when I want to do some menial analysis! One solution would be to remove labelled class from each variable in data.frame . How can I do that? Is that possible at all? If not, what are my other options? I really want to bypass reediting variables "from scratch" with as.data.frame(lapply(x, as.numeric)) and as

I have a large SPSS-file (containing a little over 1 million records, with a little under 150 columns) that I want to convert to a Pandas DataFrame. It takes a few minutes to convert the file to a list, than another couple of minutes to convert it to a dataframe, than another few minutes to set the columnheaders. Are there any optimizations possible, that I'm missing? import pandas as pd import numpy as np import savReaderWriter as spss raw_data = spss.SavReader('largefile.sav', returnHeader = True) # This is fast raw_data_list = list(raw_data) # this is slow data = pd.DataFrame(raw_data_list)

Given is the following data frame: structure(list(UH6401 = c(1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1), UH6402 = c(1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1,

I will be analysing vast amount of network traffic related data shortly, and will pre-process the data in order to analyse it. I have found that R and SPSS are among the most popular tools for statistical analysis. I will also be generating quite a lot of graphs and charts. Therefore, I was wondering what is the basic difference between these two softwares. I am not asking which one is better, but just wanted to know what are the difference in terms of workflow between the two (besides the fact that SPSS has a GUI). I will be mostly working with scripts in either case anyway so I wanted to

Update: The p-values and S.E.'s are similar between SPSS and R if I change the parameter estimation method in SPSS to 'Hybrid' and the scale parameter method to 'Pearson Chi-square'. Does anyone now how to change these settings in R and what these settings actually mean? I am trying to perform an GLM with a gamma log link function in R, to analyse a multiple imputation dataset. However, when I compare the results from the same analysis in R and SPSS they are very different. This example is in a non-imputation dataset to make things easier to interpret. The SPSS result is as follows: Parameter