Is Homicide Victims dataset repeated? I am studying an example where a Poisson model is applied to the Homicide Victims dataset. The dataset contains survey results of 1308 people who where asked about the number of homicide victims they knew. The dataset includes the response of a person (the number of homicide victims he/she knows) and his/her race. The response has minimum and maximum values of 0 and 6. The goal is to model the response using a Poisson model and assess the goodness of fit of the model.
I have two questions.

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*Is the dataset repeated? I understand that a repeated measure is a study where for each predictor variable there are repeated number of observations. In this case, I can redesign the dataset as a seven by two table (response and race) where each cell contains the number of people who know a specific number of homicide victims and have a specific race. It is important to identify if the data is repeated or not to make sure that the results of the Deviance and Pearson's Chi-Square tests are valid.

*The results of the Deviance and Pearson Chi-Square tests are as follows:
Deviance Test: Deviance = 844.7073, df = 1306, p-value = 1 and
Pearson's Chi-Square Test: Chi-Square=2279.873, p-value = 0.
So, in this case I am not sure why the p-values are critically different.


Repetition would be when you measure the response within a single same unit while varying other variables.
For instance, if you have a cyclist and you let them cycle 6 times some distance while giving them either 0, 1, 2, 3, 4, 5, or 6 candies. Then you have six different measurements but all of them with the same cyclist rather than with six different cyclists. For each cyclist you repeated the measurement, under different conditions (this contrasts to having a different cyclist for each different condition).
The difference that repetition makes is that you can model the differences between the six measurements because they were done by the same cyclist. Or with a different type of analysis (in a mixed/random-effects model), you could separate the noise into two parts, one due to the cyclist and one due to the measurement.

From your description of the homicide victims dataset it does not seem like you have a repeated measurement. You have values of predictor variables that are repeated but that is everytime with a different person out of the 1308 persons. There is no change of a predictor variable within the same person.
Copy of the table from your reference
                 Race
           Black     White
Response
0            119      1070
1             16        60 
2             12        14
3              7         4
4              3         0
5              2         0
6              0         1

However, in some sense, you do have some sort of repeated measures here. The observations of the number of responses 0, 1, 2, 3, 4, 5, 6 are done within the same race category populations.
It would, for instance, be a difference when you where performing the survey in different cities and in city A you observe the number of 0 response among white respondents, in city B you observe the number of 1 response among white respondents, in city C you observe the number of 2 response among white respondents, etc.
