Add-Ons Statistics for Data Analysis
Add-Ons are additional functionalities or shortcuts included in the Statistics for Data Analysis solution, designed and created by our team of professionals specialising in Data Analysis.
The strong experience gained in the field of Data Analysis, the in-depth knowledge of IBM SPSS Statistics and the constant collaboration with our customers has allowed us to create new functionalities not included in IBM SPSS Statistics, with the aim of:
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Providing you with a single tool to work with, so you don't have to move from one software to another depending on the need for analysis, saving you time.
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Keeping the graphical interface intuitive, so that you can concentrate on the analysis, avoiding learning specific programming languages.
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Integrating procedures created and suggested by the collaboration with our customers, to facilitate and automate your analysis activities.
Do you have an idea, something you think is missing in SPSS Statistics, that you would like to see implemented as an Add-On to conveniently call up from the software menu? Our team of professionals is ready to welcome your suggestions: write to us at statistics@spss.it
The Add-Ons are automatically installed together with IBM SPSS Statistics and can be found in the various menus:
Data
Analyse
Graphs
Below is the complete list of Add-Ons available today.
Our R&D division is constantly developing new features designed to deliver real value.
Forest Plot
Create Forest Plot charts for meta-analysis, providing a clear visual summary of the results from multiple studies.
It compares findings across different studies quickly and intuitively.
Delete Days
Remove any chosen number of days from a date variable.
Tree Map
A chart that displays hierarchical data using nested rectangles.
The size of each rectangle is proportional to a numerical variable, enabling large volumes of structured data to be visualised in a compact and intuitive way.
Stratified Sampling
It applies stratified sampling by dividing the population into homogeneous subgroups for more representative data selection.
With this procedure you can produce more balanced and meaningful samples.
Automatic ID
This procedure allows cases to be duplicated a number of times equal to the value of a numeric variable.
Duplicate Cases
This procedure allows cases to be duplicated a number of times equal to the value of a numeric variable.
Split Strings
It allows a string variable to be broken down into several parts by identifying a character within the string itself.
Add Days
It allows you to add any number of days to a variable in date format.
Contingecy Tables
With this, you can customise the contingency tables, whose data are automatically imported into a new dataset, ready for subsequent analysis.
Tables for Multiple-choice Sets
This procedure allows you to customise the tables for multiple-choice sets via a dialogue box.
RSVP Chart
It is a bar graph superimposed with a graphic element to display the bar-on-bar variation, horizontally.
Ladder Plot
This is a graph usually used to visualise the effect of a treatment on the same set of subjects, before and after treatment.
Replace Outliers
This procedure replaces missing values with the average of the values of the group to which they belong.
Keep Information
This procedure allows cases to be deduplicated by keeping those cases that contain more information.
String Deduplication
It is possible to concatenate a list of string variables while retaining, on a case-by-case basis, only the unique values of the string variables.
Text Extraction
This procedure allows a string variable to be split into two parts, by identifying a character in the string.
File Division
This procedure is useful for dividing the file into sub-files based on the values assumed by a user-defined variable.
Add 60 Days
Procedure for adding 60 days end of month to a variable in date format.
Split Random Files
Procedure for randomly extracting two distinct sets of cases from a single file.
Exclude Outliers
Procedure to obtain a data file containing only those cases that belong to the range (average (control variable) -/+ n_times the standard deviation).
Remove Duplicates
Procedure that generates a data file containing only those cases that are NOT duplicated. Cases are selected by choosing one or more control variables to identify duplicate cases.
Case Validation
You can generae a data file containing only those cases that comply with a set of constraints. Cases are selected by choosing one or more control variables and their respective constraints. In this procedure, constraints are placed on at least two variables.
Simple Sample Base
You can determine the sample size in order to obtain results that reflect the survey population with a certain degree of accuracy.
💡The next Add-on...
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