Living in the Big Pond: Adding the Neighborhood as a Frame of Reference for Academic Self-Concept Formation

This data deposit contains all analysis files that are needed to replicate the empirical results of the manuscript entitled,

"Living in the Big Pond: Adding the
Neighborhood as a Frame of Reference for Academic Self-Concept Formation".<br>Analysis files comprise a master .R-script that executes further lower-order .R-scripts (separately for each of the two waves of our analysis data). From the lower-order .R-scripts, various three-level multilevel models are run via Mplus. This is done by calling the mplus-automation package (which must be installed in advance) from R.<br><br>Underlying data is the German National Educational Panel Study (NEPS; Blossfeld et al., 2011), Starting Cohort 3 (SC3). NEPS is a longitudinal multi-cohort study that
includes information on individual students (e.g., academic self-concept,
standardized achievement, socioeconomic background), learning environments
(i.e., class identifiers that enable us to build reliable achievement
aggregates), and neighborhood conditions (e.g., social status, income,
employment).
This study established a representative sample of children attending fifth
grade in Germany in the school year of 2010/11. SC3 is based on a multistage
sampling procedure that sampled schools as the first step and selected all
students from two classes of each school in the second step. <br><br>

Within the NEPS framework, neighborhood
characteristics are provided by the commercial company microm consumer
marketing (Schönberger &amp; Koberg, 2017).

We used neighborhood characteristics on the 8-digit postal code (PLZ8)
level, thus being able to use more fine-grained neighborhood-level information
than the 5-digit (PLZ5) level which is common in Germany. The PLZ8 system divides geographical space into
neighborhoods comprising on average 500 households.<br>We used both wave 1 of NEPS-SC3 obtained between 2010/11 (5th-Grade students) and wave 5 obtained between 2014/15 (9th-Grade students). Our analyses relied on release 9.0.0 of NEPS-SC3 (doi:10.5157/NEPS:SC3:9.0.0). <br><br>As the fine-grained neighborhood-level information could be used to identify single students, parents, or teachers within specific neighborhoods, NEPS data enriched by neighborhood information can only be analysed on-site at the data hosting instition: <br><br>Leibniz Institute for Educational TrajectoriesWilhelmsplatz 3<br>
96047 BambergGermany<br><br>Readers who are interested to replicate our findings need to get in touch with the <br>Leibniz Institute for Educational Trajectories in order to <br><br>a) sign a data usage agreement for on-site analyses, <br>b) participate in a data usage training, and finally <br>c) set up an appointment to gain on-site access to the original data. <br><br>It will be necessary to adjust the paths linking to the original data in our .R-files to the user's specific needs. <br><br><b>For further information please consult the ReadMe.txt file in our analysis files ZIP folder entiteld, "Analysis_Files_Living_in_the_Big_Pond.zip".</b><br>Funding information: The NEPS was launched in 2009 and funded as a research project by the Federal Ministry of Education and Research (BMBF). Since 2014, the NEPS has been continued at the Leibniz Institute for Educational Trajectories. Only five years after its founding, the NEPS has thus been transformed from a temporary research project into an infrastructural institution with permanent funding within the framework of federal and state funding.<br>