The Observer XT
Integrated visualization of your data can be very helpful in the beginning steps of analysis. It gives you a good feel for the data.
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, you can perform a lag sequential analysis to analyze the order of events and a reliability analysis to measure the agreement between two or more raters, for example.
The publication power of The Observer XT
The Observer XT is mentioned in thousands of publications across behavioral research domains. This pie chart gives you an idea of the main domains that are researched using The Observer XT.
Click on the pie chart to go to the current list of publications in Google Scholar.
Clear visualization of data streams
The analysis of data often begins with visualizing the event log, one or more videos, audio, and physiological data streams. All data streams are displayed alongside and play in perfect sync. Visualization creates a direct reference between video, audio, and other data: a great tool for quality improvement.
By visualizing the data streams, you can easily see and present what you have collected. The visualizations can be used as figures in your publication or presentation.
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Integrating multiple data streams
To get a more complete picture of the phenomena that you are studying, combining different types of data will benefit your research. The Observer XT allows you to import, synchronize, and analyze data from many different streams, such as eye tracking, facial expressions, and physiology.
This White paper will show how logged events can be combined and synchronized with external data by using The Observer XT.
Explore your results
If you want to find a specific comment quickly, you can use the advanced find functionality. You can search through all or part of your observations to find:
The software provides you with a list of all the events that meet your criteria. This list contains start times, stop times, and durations of each event. You can click on the result and be brought to the right observation, or export the list of results to a spreadsheet program of your choice.
Sophisticated data selection
You can build elaborate filters based on combinations of independent variables, behaviors, physiological data, and time criteria. Examples of independent variables are 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 relevant data with the powerful graphical data selection tool
- Select events based on their duration
- Analyze large groups of observations at once, saving a lot of time
- Copy data profiles. For example, easily copy-paste the same selection boxes for male subjects as you had already designed for female subjects
Avoid observer bias
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 in which you can easily spot the disagreements between two observers (or observations of the same scene). You can compare an unlimited number of pairs, and each pair is presented separately so that results are clear and quickly available.
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 SPSS or 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.