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Roland
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(1 + year | ID0) specify a random intercept and a random slope, both grouped by ID0, and additionally their correlation. See the cheat sheet for an explanation of the syntax.

15 unique IDs times (intercept + slope + correlation) gives 3045 random effects. You don't have sufficient observations to support the model.

(1 + year | ID0) specify a random intercept and a random slope, both grouped by ID0. See the cheat sheet for an explanation of the syntax.

15 unique IDs times (intercept + slope) gives 30 random effects. You don't have sufficient observations to support the model.

(1 + year | ID0) specify a random intercept and a random slope, both grouped by ID0, and additionally their correlation. See the cheat sheet for an explanation of the syntax.

15 unique IDs times (intercept + slope + correlation) gives 45 random effects. You don't have sufficient observations to support the model.

replaced http://stats.stackexchange.com/ with https://stats.stackexchange.com/
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(1 + year | ID0) specify a random intercept and a random slope, both grouped by ID0. See the cheat sheetcheat sheet for an explanation of the syntax.

15 unique IDs times (intercept + slope) gives 30 random effects. You don't have sufficient observations to support the model.

(1 + year | ID0) specify a random intercept and a random slope, both grouped by ID0. See the cheat sheet for an explanation of the syntax.

15 unique IDs times (intercept + slope) gives 30 random effects. You don't have sufficient observations to support the model.

(1 + year | ID0) specify a random intercept and a random slope, both grouped by ID0. See the cheat sheet for an explanation of the syntax.

15 unique IDs times (intercept + slope) gives 30 random effects. You don't have sufficient observations to support the model.

Source Link
Roland
  • 7.1k
  • 1
  • 38
  • 68

(1 + year | ID0) specify a random intercept and a random slope, both grouped by ID0. See the cheat sheet for an explanation of the syntax.

15 unique IDs times (intercept + slope) gives 30 random effects. You don't have sufficient observations to support the model.