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Other Controls in Simulation Scenarios
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| Simulation Method | Select the method used for simulations for the current scenario. The method is Randomized First Choice by default. (See the section entitled, "Market Simulator Models" for more details about the different simulation methods.)
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| Operating Mode | The default mode is Simulation. You can specify Sensitivity mode, which is a way of processing in batch multiple simulation runs that are variations of the current scenario. For example, you may wish to see how varying all levels of price for Product 1 affects its share relative to a fixed set of competitors. Rather than run the same simulation over and over again for all levels of price for Product 1, you can specify Sensitivity mode, and choose Product 1 as the Sensitivity Product, and Price as the Sensitivity Attribute.
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| Respondents to Include | If you are using part-worth utilities from a method other than logit, you can specify the respondents to include in the simulation. If you are using aggregate utilities (from Logit), this option is not available.
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| Respondent Weights | If you are using individual-level utilities (from ACA, CVA, ACBC or CBC/HB), you can specify the respondent weights to be applied in the simulation. If you are using aggregate utilities (from Logit or Latent Class), this option is not available.
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| Apply External Effects | In some situations, you may want to adjust the share given to a particular product by some external factor. For example, perhaps that product is only available in half of the markets relative to the other products. In that case, you can check the Apply External Effects box. When this box is chosen, a new column appears in the product specification grid labeled "External Effect." All external effects are initially set to unity (1). To adjust the shares to account for a given product only being available in half of the markets, you might specify an external effect of 0.5 for that product, and leave all other products with external effects of unity (1).
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| Advanced Settings | When you click this button, a dialog appears that lets you define additional settings:
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| Correlation Cutoff | If you are using individual-level utilities generated by ACA, CVA, ACBC or CBC/HB, a measure of fit is provided indicating the relative consistency of each respondent's utilities. You can select a value used as a cutoff for excluding respondents that are at or below that threshold for consistency.
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| Exponent | The exponent tunes the overall "flatness" or "steepness" of the share results (see discussion earlier regarding the Exponent). It has effect only for the Share of Preference models and Randomized First Choice.
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| "None" Weight | If you are analyzing data for a CBC study that included a "None" option, this lets you specify the weight applied to the None utility. By default, it is zero (no "None" share computed). (See discussion earlier regarding the None weight for more direction.)
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| Unacceptable | If you are using data from an ACA study and if you asked the
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| Extrapolation | "Unacceptables" section, you can tune how low the utility should be for unacceptable levels. This percentage determines the degree of extrapolation when assigning the utility of "Unacceptable" levels. The extrapolation is customized for each respondent as a projection from the worst level of each attribute. The constant subtracted from the worst level within that attribute is determined as a percentage of the average differences between best and worst levels across all attributes for that respondent. The default is 20%. To use this setting properly, you should tune the extrapolation to best fit holdout choices/observations. Please note that the Unacceptable Extrapolation you set has a direct bearing on the importance of each attribute, and also alters the part-worth utilities.
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| Individual Results to File
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| If you are running simulations using part-worth utilities generated by a method other than logit, you can save the estimated shares of preference for each individual to a text-only file for analysis in another software package. This can be helpful, for instance, if you want to identify particular respondents that prefer (or do not prefer) a certain product.
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| Display Utilities
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| Controls whether the utilities for each attribute level (or interaction terms) are displayed in the output. The utilities displayed are rescaled by a method called Zero-Centered Diffs. The diffs method rescales utilities so that the total sum of the utility differences between the worst and best levels of each attribute across attributes (main effects) is equal to the number of attributes times 100. Note: the average part-worth attribute utilities are influenced by the number of respondents in the simulation and respondent weighting, but are not affected by the product specifications you enter. Please see an earlier section entitled, "Interpeting Conjoint Analysis Data" for more information about interpreting utilities.
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| Display Importances
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| Checking this option tells the Market Simulator to include a summary of attribute importances in the simulation output. The importance of an attribute is defined as its weight, or the maximum influence it can have on product choice, given the range of attribute levels defined in the study. In other words, an attribute's importance is an indicator of the amount of influence an attribute may have in simulations. Attribute importances are only accurate when individual- or segment-level utility data are available (such as computed under Latent Class, ACA, CVA, ACBC or Hierarchical Bayes). Aggregate importances from logit can be misleading if respondents disagree about the order of preference of levels within an attribute. Please see an earlier section entitled, "Interpeting Conjoint Analysis Data" for more information about interpreting importances.
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