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How to Use SPSS Portable 17 for Predictive Modeling and Text Analysis



One of the first tasks in any research project is reading in data. import spss allows us to bring IBM SPSS files (version 16 or higher) and compressed IBM SPSS files (version 21 or higher) into Stata. We can import the entire dataset or only a subset of it. Dates, value labels, and missing values are all converted properly from SPSS to Stata format.




Spss Portable 17




We primarily distribute data files in eight data formats: three plain text formats (column-delimited ASCII, comma-delimited ASCII, and tab-delimited ASCII), two SAS formats (SAS XPORT and CPORT files), two SPSS formats (SPSS SAV and portable files), and the single Stata data format. Virtually every data file is available in a plain text format. We also supply many data files in one or more of the other formats.


We distribute two types of SPSS data files: SPSS SAV files written by the SPSS save command and SPSS portable files written by the SPSS export command. Both types of data files include variable labels and usually include value labels and missing value definitions.


SPSS setup files can be used to generate native SPSS file formats such as SPSS system files and SPSS portable files. SPSS setup files produced by generally include the following SPSS sections. Click on each section to see an example taken from ICPSR 6512 (Capital Punishment in the United States, 1973-1993).


PSPP is currently the most viable open source GNU alternative to SPSS which is almost essential for any social sciences researcher. The ability to carry it in a portable hard disk or usb drive would be a god-send.


The user-written Stata ado-file usespss can be used to read SPSS data into Stata. Both compressed and non-compressed SPSS files can be read. The usespss command is currently only available for 32-bit installations of Stata. There is a beta version for 64-bit installations which can be installed in 64-bit Stata with the command


Stata version 9.2 or higher is required. You should carefully read the help file associated with usespss before using the command for the first time. For more information regarding this command, please see _faq.html .


First, use the search command to find and download the usespss command (see How can I use the search command to search for programs and get additional help? for more information about using search).


And if you want to remove the formats from the mix, you can "flatten" the data set so that the formatted values become the actual values within the data. The data might lose some fidelity in the process (as the formatted values might be less precise than the underlying raw values), but the data set is then more portable


And if you want to remove the formats from the mix, you can "flatten" the data set so that the formatted values become the actual values within the data. The data might lose some fidelity in the process (as the formatted values might be less precise than the underlying raw values), but the data set is then more portable. I'll share a technique for that in a different article.


Hi @lijunchen - you can turn your SPSS-labels-turned-SAS-formats into SAS data sets. Use the PROC FORMATS and CTLOUT= option as I showed in a previous comment. That data set can then be used in another PROC FORMATS step with the CTLIN= option if you ever need to rebuild it. That's the standard way to keep SAS format definitions portable across systems and different operating systems. Open or PROC PRINT the data set to see the format definition rules.


SPSS has also defined a "portable" format (see SPSS_por_ASCII) designed for transferring datasets between versions of SPSS on different platforms. However, as early as 1999, experts on discussion forums were recommending the use of SPSS "system" (.sav) files for interchange instead of .por files. See, for example, a comp.soft-sys.stat.spss discussion thread, which suggests that SPSS_sav files had been platform-independent since SPSS version 6.0, which PC Magazine, June 14, 1994 indicates was current in 1994. SPSS documentation has also indicated that SPSS_sav files are platform independent. For example, Overview (EXPORT command) from the manual for SPSS Statistics, version 21, states, "In most cases, saving data in portable format is no longer necessary, since IBM SPSS Statistics data files should be platform/operating system independent."


ICPSR's Guide to Social Science Data Preparation and ArchivingPhase 6: Depositing Data states, "If a dataset is to be archived, it must be organized in such a way that others can read it. Ideally, the dataset should be accessible using a standard statistical package, such as SAS, SPSS, or Stata. Three common approaches to data file preparation are: (1) provide the data in raw ASCII format, along with setup files to read them into standard statistical programs; (2) provide the data as a system file within a specific analysis program; or (3) provide the data in a portable file produced by a statistical program. Each of these alternatives has its advantages and disadvantages."


SAVE OUTFILE='c:\spss_syntax\fred.sav'.Saving the data as an SPSS portable fileOccasionally the need may arise to save the data as an SPSS portable file in order for the data to be readable by a previous version of SPSSor by certain other statistical packages (eg. SAS). The command is EXPORT OUTFILE="path name\file name". The standard extension is .por.Example


PSPP can import Gnumeric and OpenDocument spreadsheets, Postgres databases, comma-separated values and ASCII files. It can export files in the SPSS 'portable' and 'system' file formats and to ASCII files. Some of the libraries used by PSPP can be accessed programmatically; PSPP-Perl provides an interface to the libraries used by PSPP.


Data for manuscript "Disgust sensitivity is not associated with health in a rural Bangladeshi sample", consisting of an R analysis code, .por data file. (spss portable), and disgust scale in Bengali and English.


Therefore, the aim of our work was to establish the reproducibility and repeatability of a portable OCT system in measuring CCT at different PMIs in human corpses, and to quantify the temporal range of reliability of the method.


Conversely, portable OCT system can overcome all these limitations. Its characteristics of easy handling and portability on the site where the corpse lies, the ability to record high-resolution scans for monitoring changes, the ability to acquire in a fast and non-contact mode, make OCT imaging an ideal tool in the field of corneal transplantology and forensic sciences. In fact, the present study demonstrates that this high-technology instrument can be reliably used for corneal pachymetric measurements in supine subjects and during the post mortem period, i.e. without visual fixation and normal physiology/architecture of the examined tissue. The repeatability coefficient varied from 0.3 to 1.7% and the reproducibility coefficient varied from 0.3 to 1.6% throughout the overall experiment time span. Furthermore, the values of the different ICCs were also high during the different PMIs, thus demonstrating the high repeatability and reproducibility of the present OCT approach.


In summary, we have demonstrated for the first time the excellent reliability of corneal pachymetry in human cadavers using a portable OCT system, as well as the existence of different behaviors of the related tissues on the basis of eye opening mode. Concluding, it is possible to state that this device should be valuable for corneal explantation or, in general, for corneal transplantology, and for forensic sciences.20


Abstract:This study developed a device measuring the X-ray source-detector angle (SDA) and evaluated the imaging performance for diagnosing chest images. The SDA device consisted of Arduino, an accelerometer and gyro sensor, and a Bluetooth module. The SDA values were compared with the values of a digital angle meter. The performance of the portable digital radiography (PDR) was evaluated using the signal-to-noise (SNR), contrast-to-noise ratio (CNR), spatial resolution, distortion and entrance surface dose (ESD). According to different angle degrees, five anatomical landmarks were assessed using a five-point scale. The mean SNR and CNR were 182.47 and 141.43. The spatial resolution and ESD were 3.17 lp/mm (157 μm) and 0.266 mGy. The angle values of the SDA device were not significantly difference as compared to those of the digital angle meter. In chest imaging, the SNR and CNR values were not significantly different according to the different angle degrees. The visibility scores of the border of the heart, the fifth rib and the scapula showed significant differences according to different angles (p 2ff7e9595c


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