Real Time Data Visualization

Reliable and Valid (Masked) Visual Analysis

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Graphs

Real time graphical data display

User friendly and reliable

Access anytime, anyplace

Data sharing

Invite collaboraters to join your project

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GETTING STARTED WITH A NEW PROJECT
The project manager creates a new project by clicking on "Create New Project". The manager will receive two unique PIN codes. One PIN code for the intervention team and one code for the analysis team. The project manager distributes the appropriate PIN code to the project members depending on the specific role (interventionist or analyst). Members can sign in as either analyst or interventionist using the unique PIN. Members can only take one role per project

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First, choose a name for the newly created project. Second, choose your role in the project (interventionist or analyst). Third, choose the type of research design (response-guided or fixed criterion)

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SPECIFY CRITERIA
The applications allows to specify up to seven participants. Multiple members can be part of the intervention team and the analysis team. In this screen, the research criteria that both teams agree upon are specified. The specification of outlier detection is optional (the ""+/- slope" criterion refers to observing a slope in the oposite direction of the expected change)

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Specify a name for the outcome variable that you are going to measure repeatedly over time. Assign a value for the upper limit of your outcome variable.

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Choose a name for your participants.

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If a fixed criterion design is chosen, the intervention team is guided to a new screen. The intervention team selects a pre-determined order of participants intervetion start points. Because this is a fixed criterion design, the MVA is limited to summary analysis at the end of the data collection.

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The project manager distributes the unique codes to the other members of the project (to analyst[s]/interventionist[s]). The project manager will be automatically signed in when clicking on "Return to research project", either as part of the intervention team or analysis team (depending on the chosen role while creating the project). Members can only be assigned one role for the duration of the project.

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You will be able to navigate all your assigned or created research projects under two different tabs, namely Analyst and Interventionist.

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The intervention team starts collecting the data. The interventionist immediately plugs in the data by clicking on the specific participant.

Once the intervention team completed data collection for all the participants, the status changes to "waiting for final decision". During the experiment, the intervention and analysis team can click on "Details" on the top right of the screen. The details screen provides an overview of the criteria specified at the beginning (when creating the project).

Once the analyst team made the decision "next phase" (which means "start the intervention"),a participant needs to be randomly selected. This can be accomplished by clicking on "Participant Selection". Without selecting a random participant to start the intervention, the experiment cannot proceed. The MVA application randomly suggests a participant to start the intervention with.

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The members of the analysis team will be able to see the graphical display of the data in real time. Everytime the intervention team collects new data and plugs it in, the analysis team will see immediately the updated graphs. The analysis team has the option to see the criteria specified in the beginning ("Criteria"), keep track of the chosen participant order ("Notes") and see the graphs in a bigger display ("Switch"). Once the analysis team gets a notification that the data collection for the current phase is completed, a decision needs to be made. The analysis team will get a notification to make a decision. The decision can be made by clicking on the "Decision" button.

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The analysis team is directed to a decision screen. The analyst[s] will need to make a decision (starting the intervention for another participant or further data collection is needed)

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If the analysis team requests more data, a short explanation needs to be given and submitted.

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The analysis team has the option to keep track of the expected order of participants that received the intervention. The "Note" button can be used for this purpose.

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In case there are multiple members part of the analysis team and there is a discrapancy (intervening versus more data collection), the analysts will be directed towards a new screen displaying an overview of the decisions made by all the analysis team members.

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Before making a new decision, the analysts will discuss the discrapancy to find consensus. Thoughts can be shared using the chat function at the bottom of the screen.

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After the data collection is completed for all the participants, all the members of the analysis team will be guided towards a final decision screen. The analyst[s] will guess the order in which the interventions were introduced to the participants.

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The p-value is calculated and displayed. The p-value is calculated as following: (the number of guesses of the random order of participants) divided by (the number of possible orders, which is the number of participants factorial). If there are multiple members part of the analysis team, we suggest an adjusted calculation. In that case, the p-value is (the average number of guesses of the random order of the participants) divided by (the total number of participants factorial)

Additional Sources

Byun, T.M., Hitchcock, E., & Ferron, J.M. (2017). Masked visual analysis: Minimizing type I error in response-guided single-case design for communication disorders. Journal of Speech, Language, and Hearing Research, 60, 1455-1466.
Ferron, J.M., Joo, S.H., & Levin, J.R. (2017). A Monte-Carlo evaluation of masked-visual analysis in response-guided versus fixed criteria multiple-baseline designs. Journal of Applied Behavior Analysis, 520, 701-716.

Moeyaert, M., Bursali, S, & Ferron, J. (2020). SCD-MVA: A mobile application for conducting single-case experimental design research during the pandemic. Special issue “COVID-19 and Human Behavior with Emerging Technologies”. Human Behavior and Emerging Technologies. doi: 10.1002/hbe2.223

Download Whitepaper Download Dataset

Semih BURSALI

Ph.D. Student
sbursali@albany.edu

Mariola Moeyaert

Associate Professor
mmoeyaert@albany.edu

Derek Cacciotti

Software Developer
dcacciotti@albany.edu

John Ferron

Professor
ferron@usf.edu