Data analysis

The Observer XT: sophisticated data selection, clear visualization of data, powerful data analysis, and versatile because of all its export and import functions.


Clear visualization of data
The analysis of data often begins with visualizing the event log, one or more videos, and physiological data streams. All data streams are displayed alongside and play in perfect sync. Visualization creates a direct reference between video and data: a great tool for quality improvement.

  • Continuous recording - the track of continuous scored events is visualized as a horizontal bar in which different colors represent different active states.
  • Instantaneous sampling - samples are visualized as dots. The colors correspond with the colors of the continuous scored behaviors and can thus be compared easily.


Sophisticated data selection
You can build elaborate filters based on combinations of independent variables, behaviors, physiological data, and time criteria, such as behaviors being active, or select subjects by independent variable. The independent variables are for labeling and filtering: for example treatment, subject ID, observer, and any other important circumstances. All data in the project is available for analysis at all times.

  • Extract only the relevant bits for each research question.
  • Filter out the relevant data with the powerful and intuitive graphical data selection tool.
  • Analyze large groups of observations at once, saving a tremendous amount of time.


Powerful data analysis
The Observer XT offers descriptive statistics of the coded behavior. Among the possible output are tables of frequencies, durations and other statistics, interaction matrices, and transition matrices. Next to that, synchrony and learning curves are analyzed. Moreover, it is with The Observer XT you can perform a lag sequential analysis to analyze the order of events.

You can also perform latency analysis. Response latency is the time between the onset of a stimulus and the initiation of the response. This latency analysis in The Observer XT enables you to investigate the relation between stimulus and response in depth.

Explore and present results
The Observer XT 10 allows you to create pie charts, scatter plots (with trendlines), or other visual representations of your results. You can easily use these illustrations for presentation purposes. Save the graph and present it in your PowerPoint presentation or research article. You can also take a snapshot of your event plot, with just a push of a button, and use this in your report or presentation.

Reliability analysis: inter-rater and intra-rater
In collaborative projects it is vital to avoid observer bias. An important tool to detect this, is reliability analysis: observations by different coders (inter-rater) are compared record by record and the software reports Cohen’s Kappa, along with a listing of agreements and disagreements. Reliability analysis is also used for intra-rater reliability, as a basic quality check.

Reliability analysis output includes a confusion matrix. It only takes a blink of an eye to see exactly which values are seen as agreements and which are not. Values that do not exactly match between observations are shown off the diagonal, to visually represent the disagreement. Agreements are indicated with a blue background color. 

Import functions
The Observer XT is an open system, allowing you to import event data from many different systems and to export data in XML format for use in other systems. The analytical powers of The Observer XT can easily be used on data from Data Acquisition Systems.

Export functions
You can easily select which data to export. Data from The Observer XT can be used in other packages for further analysis. Export the event data together with external data such as heart rate data. You can split up the results in intervals and the layout of results is completely customizable to the requirements of receiving software packages such as:

  • Theme™
  • SPSS
  • Microsoft Excel

The export to Excel functionality has been optimized, allowing you to export directly from the observation and analysis. By merging header rows, Excel format files can be imported directly into SPSS. This saves valuable time, eliminating the need to adjust the data.

A Software Development Kit (SDK) is available for developers who want to build their own modules or interfaces with other systems.