Launch Window for One Table, Stacked | JMP 13.2

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Consumer Research • Choice Models • Launch the Choice Platform • Launch Window for One Table, Stacked

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Launch Window for One Table, Stacked

Launch Window for One Table, Stacked Data Format

Select Data Table

Select or open the data table that contains the combined data. Select Other to open a file that is not already open.

Response Indicator

A column that contains values that indicate the preferred choice. A 1 indicates the preferred profile and a 0 indicates the other profiles. If respondents are given an option to select no preference, enter missing values for choice sets where no preference is indicated. See Respondent is allowed to select “None” or “No Choice”.

An identifier for the study participant.

An identifier for the choice set presented to the subject for a given preference determination.

A column which, when used with the Choice Set ID column, uniquely designates each choice set. For example, if a choice set has Choice Set ID = 1 for Survey = A, and another choice set has Choice Set ID = 1 for Survey = B, then Survey should be used as a Grouping column.

Construct Profile Effects

Add effects constructed from the attributes in the profiles.

For information about the Construct Profile Effects panel, see Construct Model Effects in the Fitting Linear Models book.

Construct Subject Effects (Optional)

Add effects constructed from subject-related factors.

For information about the Construct Subject Effects panel, see Construct Model Effects in the Fitting Linear Models book.

Firth Bias-adjusted Estimates

Computes bias-corrected MLEs that produce better estimates and tests than MLEs without bias correction. These estimates also improve separation problems that tend to occur in logistic-type models. Refer to Heinze and Schemper (2002) for a discussion of the separation problem in logistic regression.

Hierarchical Bayes

Uses a Bayesian approach to estimate subject-specific parameters. See Bayesian Parameter Estimates.

Number of Bayesian Iterations

(Applicable only if Hierarchical Bayes is selected.) The total number of iterations of the adaptive Bayes algorithm used to estimate subject-specific parameters. This number includes a burn-in period of iterations that are discarded. The number of burn-in iterations is equal to half of the Number of Bayesian Iterations specified on the launch window.

Respondent is allowed to select “None” or “No Choice”

Enters a No Choice Indicator into the model for response rows containing missing values. For the One Table, Stacked data format, the No Choice rows must contain (numeric) missing values in the Response Indicator column. The option appears at the bottom of the launch window.

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Help created on 9/19/2017