Timeline for Approaches for generating synthetic survey data with dependent answers?
Current License: CC BY-SA 3.0
7 events
| when toggle format | what | by | license | comment | |
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| Mar 16, 2015 at 3:38 | comment | added | Glen_b | If you have specified the joint distribution you can certainly calculate the conditional distribution directly, and hence sample that. | |
| Mar 13, 2015 at 16:52 | comment | added | Vass | how can the discrete values which are categorical be used in a distribution to sample for a new question? Eg. q1 answer is C, how do we sample a new value for q2 given that q1 is C? Should it be a Bayesian conditional probability? | |
| Mar 11, 2015 at 21:36 | vote | accept | Vass | ||
| Mar 18, 2015 at 20:43 | |||||
| Mar 11, 2015 at 19:42 | comment | added | Antoine R | In our case, we were doing very general simulations to show how a calibration estimator behaved. We were fine with our quantitative data drawn from a uniform. That might not be the case for you, but same method works for any kind of distribution (say, a log-normal if you're modeling salary). And you can generate non-linear links easily too : for example $X_k = \alpha \cdot e^{z_k}$ As for categorical variables, binomial suited our needs perfectly, but another discrete distribution might suit your needs better (maybe repeated Bernoulli experiments ?). | |
| Mar 11, 2015 at 19:41 | comment | added | Antoine R | Actually I assumed you needed to simulate survey data either for Monte-Carlo simulation or for demonstration/teaching purposes. Is it what you're trying to do ? Perhaps are you trying to make thorough checks about theoretical statistics, in which case you might be better off with copulas, just like Glen_b suggested. | |
| Mar 11, 2015 at 14:04 | comment | added | Vass | the variables are categorical and quantitative. So you sample the quantitative numbers there from a uniform distribution? For the categorical variables is that the Beta distribution or Binomial? I'm not sure how from either we can get a categorical sample? In the Binomial case maybe by sampling and seeing which side of the distribution we are in to choose between (1or0)? These relationships are linear, is there an easy way to get non-linear relationships? Eg. XOR type relationships? | |
| Mar 11, 2015 at 13:02 | history | answered | Antoine R | CC BY-SA 3.0 |