Imputes univariate missing data using a two-level normal model

`mice.impute.2l.norm(y, ry, x, type, wy = NULL, intercept = TRUE, ...)`

y

Vector to be imputed

ry

Logical vector of length `length(y)`

indicating the
the subset `y[ry]`

of elements in `y`

to which the imputation
model is fitted. The `ry`

generally distinguishes the observed
(`TRUE`

) and missing values (`FALSE`

) in `y`

.

x

Numeric design matrix with `length(y)`

rows with predictors for
`y`

. Matrix `x`

may have no missing values.

type

Vector of length `ncol(x)`

identifying random and class
variables. Random variables are identified by a '2'. The class variable
(only one is allowed) is coded as '-2'. Random variables also include the
fixed effect.

wy

Logical vector of length `length(y)`

. A `TRUE`

value
indicates locations in `y`

for which imputations are created.

intercept

Logical determining whether the intercept is automatically added.

...

Other named arguments.

Vector with imputed data, same type as `y`

, and of length
`sum(wy)`

Implements the Gibbs sampler for the linear multilevel model with heterogeneous with-class variance (Kasim and Raudenbush, 1998). Imputations are drawn as an extra step to the algorithm. For simulation work see Van Buuren (2011).

The random intercept is automatically added in `mice.impute.2L.norm()`

.
A model within a random intercept can be specified by ```
mice(...,
intercept = FALSE)
```

.

Kasim RM, Raudenbush SW. (1998). Application of Gibbs sampling to nested variance components models with heterogeneous within-group variance. Journal of Educational and Behavioral Statistics, 23(2), 93--116.

Van Buuren, S., Groothuis-Oudshoorn, K. (2011). `mice`

: Multivariate
Imputation by Chained Equations in `R`

. *Journal of Statistical
Software*, **45**(3), 1-67. https://www.jstatsoft.org/v45/i03/

Van Buuren, S. (2011) Multiple imputation of multilevel data. In Hox, J.J.
and and Roberts, J.K. (Eds.), *The Handbook of Advanced Multilevel
Analysis*, Chapter 10, pp. 173--196. Milton Park, UK: Routledge.

Other univariate `2l`

functions: `mice.impute.2l.bin`

,
`mice.impute.2l.lmer`

,
`mice.impute.2l.pan`