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amoeba
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Can anyone help me understand the difference in the following two model parameterizations please?

I have a repeated measures from clusters, over several years, and I expect the cluster effect to vary each year. Year is coded as a factor, with '1' as reference level. I have tried the following:

mod1<mod1 <- lmer(y ~ x + year + (year|cluster))

and

mod2<mod2 <- lmer(y ~x~ x + year + (1|cluster:year))

My first example specifies the following random effects:

ranef(mod1)
$cluster
    (Intercept)  year2         year3        year4         year5
AA   0.03721015  0.0573160920 -0.114709171  0.1588302187  0.125329740
AB  -0.12958994 -0.0458997003  0.216455596  0.2345170893  0.248950509
AC  -5.10692972 -0.1311546328  1.130347798  2.5215580167  5.070106525
AD   0.10087455 -0.2677088515 -0.345583355 -0.2442831982 -0.257074662
....

Second one specifies:

ranef(mod2)
$`cluster:year`
              (Intercept)
AA:year2  0.0838186244
AA:year3 -0.1197284361
AA:year4  0.1944488619
AA:year5  0.1562090690

I assumed they would be equivalent, given year is a factor, but I must not understand the random effect specification of lme4lme4 well enough. Any suggestions would be appreciatedCan anyone help me understand the difference between the two parameterizations?

Can anyone help me understand the difference in the following two model parameterizations please?

I have a repeated measures from clusters, over several years, and I expect the cluster effect to vary each year. Year is coded as a factor, with '1' as reference level. I have tried the following:

mod1<-lmer(y ~ x + year + (year|cluster))

and

mod2<-lmer(y ~x + year + (1|cluster:year))

My first example specifies the following random effects:

ranef(mod1)
$cluster
    (Intercept)  year2         year3        year4         year5
AA   0.03721015  0.0573160920 -0.114709171  0.1588302187  0.125329740
AB  -0.12958994 -0.0458997003  0.216455596  0.2345170893  0.248950509
AC  -5.10692972 -0.1311546328  1.130347798  2.5215580167  5.070106525
AD   0.10087455 -0.2677088515 -0.345583355 -0.2442831982 -0.257074662
....

Second one specifies:

ranef(mod2)
$`cluster:year`
              (Intercept)
AA:year2  0.0838186244
AA:year3 -0.1197284361
AA:year4  0.1944488619
AA:year5  0.1562090690

I assumed they would be equivalent, given year is a factor, but I must not understand the random effect specification of lme4 well enough. Any suggestions would be appreciated

I have a repeated measures from clusters, over several years, and I expect the cluster effect to vary each year. Year is coded as a factor, with '1' as reference level. I have tried the following:

mod1 <- lmer(y ~ x + year + (year|cluster))

and

mod2 <- lmer(y ~ x + year + (1|cluster:year))

My first example specifies the following random effects:

ranef(mod1)
$cluster
    (Intercept)  year2         year3        year4         year5
AA   0.03721015  0.0573160920 -0.114709171  0.1588302187  0.125329740
AB  -0.12958994 -0.0458997003  0.216455596  0.2345170893  0.248950509
AC  -5.10692972 -0.1311546328  1.130347798  2.5215580167  5.070106525
AD   0.10087455 -0.2677088515 -0.345583355 -0.2442831982 -0.257074662
....

Second one specifies:

ranef(mod2)
$`cluster:year`
              (Intercept)
AA:year2  0.0838186244
AA:year3 -0.1197284361
AA:year4  0.1944488619
AA:year5  0.1562090690

I assumed they would be equivalent, given year is a factor, but I must not understand the random effect specification of lme4 well enough. Can anyone help me understand the difference between the two parameterizations?

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amoeba
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Correct specification of random coefficients Difference between (factor|group) and (1|factor:group) specifications in lme4

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Mainard
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Correct specification of random coefficients in lme4

Can anyone help me understand the difference in the following two model parameterizations please?

I have a repeated measures from clusters, over several years, and I expect the cluster effect to vary each year. Year is coded as a factor, with '1' as reference level. I have tried the following:

mod1<-lmer(y ~ x + year + (year|cluster))

and

mod2<-lmer(y ~x + year + (1|cluster:year))

My first example specifies the following random effects:

ranef(mod1)
$cluster
    (Intercept)  year2         year3        year4         year5
AA   0.03721015  0.0573160920 -0.114709171  0.1588302187  0.125329740
AB  -0.12958994 -0.0458997003  0.216455596  0.2345170893  0.248950509
AC  -5.10692972 -0.1311546328  1.130347798  2.5215580167  5.070106525
AD   0.10087455 -0.2677088515 -0.345583355 -0.2442831982 -0.257074662
....

Second one specifies:

ranef(mod2)
$`cluster:year`
              (Intercept)
AA:year2  0.0838186244
AA:year3 -0.1197284361
AA:year4  0.1944488619
AA:year5  0.1562090690

I assumed they would be equivalent, given year is a factor, but I must not understand the random effect specification of lme4 well enough. Any suggestions would be appreciated