Tanks you for your (Amir) question,

We recommend that you use HLM 2 or 3, because you only use three variables alone.

HLM is an appropriate analytical techniques for data analysis nested or hierarchical structure in which the individual observations nested within groups. Analyzing the data that is hierarchical with HLM can be used to obtain information on diversity at the group level which can not be known if the analysis is simple linear regression model. Implementation of HLM in the disciplines of education, for example on issues of intelligence and socio-economic status of students' language test scores, where students nested within schools. This study aims to establish several models HLM 2 levels and determine the best model in the case of the influence of IQ and socioeconomic status of the language test scores. HLM second level consists of two submodels are models of level 1 and level 2 models, a combination of 2 submodel into a form consisting of a combination model of fixed effects and random effects. HLM-model models built is random intercept model of level 1, level 2 models random intercept and random coefficient models. The data set is distinguished hierarchy of nested level 1 in the group at level 2, in this case the students are grouped in school. The data used in this study consisted of a response variable the results of the test with two predictor variables, level 1 is IQ and socioeconomic status of students, the predictor variables are variables level 2 -rata average socioeconomic status of each - each school.