2020
DOI: 10.1177/1073191119897122
|View full text |Cite
|
Sign up to set email alerts
|

Regression-Based Normative Data for Children From Latin America: Phonological Verbal Fluency Letters M, R, and P

Abstract: This study is part of a larger project to generate norms for letter verbal fluency test (VFT) in 3,284 children from nine Latin American countries. The letter VFT (letters M, R, and P) was administered and multiple linear regressions, including age, age2, MPE (mean parental education), MPE2, sex, and interactions were used as predictors. Results showed significant differences across countries for all scores. Age affected scores linearly except for Ecuador (P-letter), in which a quadratic effect was found. Scor… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
9
0
1

Year Published

2020
2020
2024
2024

Publication Types

Select...
6
1

Relationship

3
4

Authors

Journals

citations
Cited by 12 publications
(10 citation statements)
references
References 49 publications
(88 reference statements)
0
9
0
1
Order By: Relevance
“…The normative data that fit for the demographic variables were established through a four-step procedure, using the final regression model obtained at the end of the procedure (Rivera et al, 2019(Rivera et al, , 2020: (a) The expected test score (Ŷ i ) is computed based on the fixed effect parameter estimates of the established final regression model:…”
Section: The Effects Of Demographic Variables and The Derivation Of Nmentioning
confidence: 99%
“…The normative data that fit for the demographic variables were established through a four-step procedure, using the final regression model obtained at the end of the procedure (Rivera et al, 2019(Rivera et al, , 2020: (a) The expected test score (Ŷ i ) is computed based on the fixed effect parameter estimates of the established final regression model:…”
Section: The Effects Of Demographic Variables and The Derivation Of Nmentioning
confidence: 99%
“…Using beta values of each final regression model, four steps were followed (Rivera et al., 2021) to estimate z ‐scores false(zifalse)$( {{z_i}} )$ and percentile false(Pcifalse)$( {P{c_i}} )$ adjusted to demographical variables: (1) the predict score false(Ŷifalse)$( {{{\hat Y}_i}} )$ was computed based on the fixed effect parameter estimated of the established final regression model; (2) to estimate residual value false(eifalse)$( {{e_i}} )$ the following formula: ei=0.28emYi0.28emŶi${e_i} = \;{Y_i} - \;{\hat Y_i}$ was used; (3) residuals should be standardized using the residual standard deviation (SD e ) of the regression model: zi=ei0.28em/normalSDe${z_i} = {e_i}\;/{\rm{S}}{{\rm{D}}_e}$; and (4) to convert zi${z_i}$ to Pci$P{c_i}$, the standard normal cumulative distribution function was used if the model assumption of normality of the standardized residuals was met in the normative sample. If the standardized residuals were not normally distributed in the normative sample, the empirical cumulative distribution function of the standardized residuals was used.…”
Section: Methodsmentioning
confidence: 99%
“…Multiple regression analyses were conducted for each clustering and switching strategy following Rivera et al (2021) methodology. The full regression models were included as predictors: age, quadratic age, sex, MPE, quadratic MPE, type of school and two‐way interactions between the fixed effects.…”
Section: Methodsmentioning
confidence: 99%
See 2 more Smart Citations