Researchers and policy makers mutually inform each other (e.g. Weiss, 1977, 1979). The instrumental and conceptual (Hofstetter & Alkin, 2003) uses of educational evaluation specially need the knowledge transference from science. In this way, there have been many developments in school effectiveness research (SER) over the last 40 years, which allowed the identification and incorporation of factors of effectiveness into school improvement programs, in such a way that lead to better learning outcomes for students (e.g. Cresswell, 2004). For instance, there is a broad consensus in the literature about the indicator of educational value added as a measure of institutional performance (OECD, 2008). Nevertheless, the need to conduct SER in different countries and contexts has been recognized since in the US, the UK, the Netherlands and Australia it is where it has been mostly conducted (Peng, Thomas, Yang, & Li, 2006). Reviews on SER in developing countries (e.g. Scheerens, 2001a, 2001b; Yu, 2007) are based on studies that fail to satisfy SER methodological requirements, being of limited use either for scientific purposes or for policy and practice. Some recent articles (Ferrão & Couto, 2013a, 2013b; Ferrão, 2014) have discussed SER issues concerning two Portuguese speaking countries, Brazil and Portugal. The papers  include aspects related to the scientific properties (e.g. Teddlie, Reynolds, & Sammons, 2000), i.e. the existence of school effects, the magnitude, the consistency and the stability, but they have not addressed the topic of differential school effects. Are schools differentially effective for certain groups of students within school? Are school effects generalizable within schools? Are schools differentially effective across subject areas? These are some of the research questions addressed in this paper.

Multilevel models are applied considering student as level one unit and school as level two unit. Specifically, statistical models are specified as a traditional value-added model (Ferrão & Goldstein, 2009) and as a growth model (Ferrão, 2011). The models include student’s performance in maths/reading at the end of the year as the response variable and students’ prior achievement, socioeconomic status, gender, race/ethnic group as controlling variables.

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