View source: R/f_s3_multilevel.R

summary.rendo.multilevel | R Documentation |

`summary`

method for class "`rendo.multilevel`

".

```
## S3 method for class 'rendo.multilevel'
summary(object, model = c("REF", "FE_L2", "FE_L3", "GMM_L2", "GMM_L3"), ...)
```

`object` |
an object of class "rendo.multilevel", usually, a result of a call to |

`model` |
character string to indicate which fitted model should be summarized.
Possible values are: |

`...` |
ignored, for consistency with the generic function. |

The multilevelIV() function estimates three models, namely: the usual random effects model (REF), the fixed effects model (FE) and the hierarchical GMM model (GMM) proposed by Kim and Frees (2007). The fixed effects and the GMM estimators are calculated at each level - so in the case of a three-level model, the function estimates, besides the random effects, fixed effects models at level two (FE_L2) and at level three (FE_L3). The same is true for the GMM estimators, the multilevelIV() function will return a GMM estimator at level-three (GMM_L3) and a GMM estimator at level two (GMM_L2).

In order to facilitate the choice of estimator to be used, the `summary()`

function also returns an omitted variable test (OVT).
This test is based on the Hausman test for panel data. The OVT allows the comparison of a robust eastimator and an estimator which is efficient
under the null hypothesis of no omitted variables. Moreover, it allows the comparison of two robust
estimators at different levels.

For the model specified in argument `model`

, the `summary()`

function returns the
summary statistics of the estimated coefficients, together with the results of the omitted variable test
between the specified model and each other model.

For the model specified in argument `model`

, the function `summary.rendo.multilevel`

computes and returns
a list of summary statistics and the results of the omitted variable tests for the fitted multilevel object given in `object`

.

An object of class `summary.rendo.multilevel`

is returned that is a list using the component `call`

of argument `object`

, plus,

`summary.model` |
the model parameter with which the summary function was called. |

`coefficients` |
a |

`OVT.table` |
results of the Hausman omitted variable test for the specified model compared to all other models. |

`vcov` |
variance covariance matrix derived from the GMM fit of this model. |

The model fitting function `multilevelIV`

Function `coef`

will extract the `coefficients`

matrix and
function `vcov`

will extract the component `vcov`

.

```
data("dataMultilevelIV")
# Fit two levels model
res.ml.L2 <- multilevelIV(y ~ X11 + X12 + X13 + X14 + X15 + X21 + X22 + X23 + X24 + X31 +
X32 + X33 + (1|SID) | endo(X15),
data = dataMultilevelIV, verbose = FALSE)
# Get summary for FE_L2 (does not print)
res.sum <- summary(res.ml.L2, model = "FE_L2")
# extract table with coefficients summary statistics
sum.stat.FE_L2 <- coef(res.sum)
# extract vcov of model FE_L2
FE_L2.vcov <- vcov(res.sum)
# same as above
FE_L2.vcov <- vcov(res.ml.L2, model = "FE_L2")
```

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