Zapis dokaza metode

Hierarchical Linear Modeling

Hierarchical Linear Modeling (HLM), also known as Multilevel Modeling (MLM), is a parametric statistical method for analyzing nested or clustered data — for example students within classrooms, patients within hospitals, or employees within organizations. Formalized by Raudenbush and Bryk in their 2002 seminal text (building on work from the mid-1980s), HLM simultaneously estimates individual-level and group-level effects while correctly partitioning variance across levels.

Sources recorded, not reviewed

Izvorni zapis

Citati kopirani doslovno iz izvornog zapisa metode. Ne impliciraju nikakvu provjeru na razini tvrdnje.

Hierarchical Linear Modeling (HLM / Multilevel Modeling)

Taksonomski zapis metode · hypothesis-test / statistics

Raudenbush, S.W. & Bryk, A.S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. · ISBN 978-0761919049
Hox, J.J. (2010). Multilevel Analysis: Techniques and Applications (2nd ed.). Routledge. · DOI 10.4324/9780203852279

Otvori cijelu metodu

Uređene tvrdnje

Tvrdnje pohranjene u knjigu dokaza, svaka s vlastitom procjenom.

Nema uređenih tvrdnji

Ovaj prikaz ne izmišlja procjenu tvrdnje kada knjiga dokaza nema nijednu.

Povezane metode

Generirano iz grafa metode i prikazano kao strojno predložene relacije — ne implicira se nikakva tvrdnja dokaza.

Used in the same domainMixed Effects Modelmachine-suggested · Relational suggestion, not evidence.Same method familyOne-way ANOVAmachine-suggested · Relational suggestion, not evidence.Same method familyRepeated-measures ANOVAmachine-suggested · Relational suggestion, not evidence.Used in the same domainSEMmachine-suggested · Relational suggestion, not evidence.