Important: Read this before posting to this forum

  1. This forum is for questions related to the use of Apollo. We will answer some general choice modelling questions too, where appropriate, and time permitting. We cannot answer questions about how to estimate choice models with other software packages.
  2. There is a very detailed manual for Apollo available at http://www.ApolloChoiceModelling.com/manual.html. This contains detailed descriptions of the various Apollo functions, and numerous examples are available at http://www.ApolloChoiceModelling.com/examples.html. In addition, help files are available for all functions, using e.g. ?apollo_mnl
  3. Before asking a question on the forum, users are kindly requested to follow these steps:
    1. Check that the same issue has not already been addressed in the forum - there is a search tool.
    2. Ensure that the correct syntax has been used. For any function, detailed instructions are available directly in Apollo, e.g. by using ?apollo_mnl for apollo_mnl
    3. Check the frequently asked questions section on the Apollo website, which discusses some common issues/failures. Please see http://www.apollochoicemodelling.com/faq.html
    4. Make sure that R is using the latest official release of Apollo.
  4. If the above steps do not resolve the issue, then users should follow these steps when posting a question:
    1. provide full details on the issue, including the entire code and output, including any error messages
    2. posts will not immediately appear on the forum, but will be checked by a moderator first. This may take a day or two at busy times. There is no need to submit the post multiple times.

Search found 10 matches

by Patrick_K
30 Jan 2024, 20:59
Forum: Estimation results
Topic: Interpretation of coefficients
Replies: 3
Views: 498

Re: Interpretation of coefficients

1. So it also cannot be said that they are more sensitive to the one attribute than to the other? 2. But within an Latent class model where b_1 is 0.69 for class A and b_1 is 0.12 for class B it can indeed be derived that for respondents in class A b_1 has higher positive influence on utility than f...
by Patrick_K
26 Jan 2024, 14:58
Forum: Estimation results
Topic: Interpretation of coefficients
Replies: 3
Views: 498

Interpretation of coefficients

Dear Stephane, just a general question to recheck: If I have two different coefficients for two different attributes: b_1 -0.54 b_2 -0.13 Can it be derived from that that the b_1 has more influence on the utility for the respondents so that it is more important to the respondents than b_2 (even if t...
by Patrick_K
09 Mar 2023, 12:55
Forum: Model specification
Topic: Dummy vs. linear coding
Replies: 3
Views: 3191

Re: Dummy vs. linear coding

Hi Stephane, thank you very much for checking the code. Did I get your hints right when rewriting the code like below? V[["SQ"]] = b0 + b_Beitr*Beitr_1 + b_HoeheEEE*HoeheEEE_1*( HoeheEEE_1!=4) + b_HoeheEEEunb*HoeheEEE_1*(HoeheEEE_1==4) + b_ZeitEEE*ZeitEEE_1*( ZeitEEE_1!=4)+ b_ZeitEEEunb* Z...
by Patrick_K
07 Feb 2023, 16:36
Forum: Model specification
Topic: Dummy vs. linear coding
Replies: 3
Views: 3191

Dummy vs. linear coding

Dear Stephane, I have a question on coding of attributes. Our experiment has three attributes: A1 has only numerical levels, A2 and A3 have three numerical levels and one nominal level each. In my first estimation approach I have dummy-coded A2 and A3. We have now tried to separate A2 and A3 and est...
by Patrick_K
19 Sep 2022, 10:32
Forum: Data preparation, processing and pre-estimation analysis
Topic: Data cleaning
Replies: 5
Views: 4408

Re: Data cleaning

Are there any specific guidelines how this can be judged or any papers you can recommend on dealing with inconsistent respondents?
by Patrick_K
17 Sep 2022, 11:41
Forum: Data preparation, processing and pre-estimation analysis
Topic: Data cleaning
Replies: 5
Views: 4408

Re: Data cleaning

Dear Stephane,

thank you for this important advice.
Though, it might be the same with irrational respondents (not answering two same fixed choice tasks in the same way), isn´t it?
So not deleting them from the sample just because they failed the test for completeness axiom?

Thank you very much.
by Patrick_K
11 Sep 2022, 14:05
Forum: Data preparation, processing and pre-estimation analysis
Topic: Data cleaning
Replies: 5
Views: 4408

Data cleaning

Hi there, I am trying to clean my data at the moment. So far, I´ve looked for straighlining within the choice tasks and other survey questions and also for speeders who spend less than 3 seconds on one choice task. Furthermore, I took a look at suspicious answers to open qualitative questions in the...
by Patrick_K
21 May 2022, 16:12
Forum: Post-estimation analysis/use of results
Topic: Predictions and marginal effects
Replies: 7
Views: 5775

Re: Predictions and marginal effects

When working with the predictions function I had some questions: I. I tried to compute predictions for a 10% price change in comparison to fixed status quo price level. I used the following code (once with Price_SQ, once with Price_Alt1, once with Price_Alt2): _____ predictions_base = apollo_predict...
by Patrick_K
16 May 2022, 17:41
Forum: Post-estimation analysis/use of results
Topic: Predictions and marginal effects
Replies: 7
Views: 5775

Re: Predictions and marginal effects

Hi Stephane, thank you very much for your prompt reply. I will try to do the predictions with the recommended example. With regards to the p-value I was looking for an indicator for the correlation of the individual decisions among themselves, so how much of the variance can be explained by the rand...
by Patrick_K
14 May 2022, 14:44
Forum: Post-estimation analysis/use of results
Topic: Predictions and marginal effects
Replies: 7
Views: 5775

Predictions and marginal effects

Hi there, I am new to apollo and have two questions: 1. Is there a way of reporting a p-value for the model itself? I just find the p-values for my parameters but not for the model itself. I am estimating a MNL model. 2. I have one price attribute and two dummy coded other attributes; my experiment ...