summary(svyglm) Pr (> | t |) ?

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Dear Diana,

The Anova() function in the car package will produce a Wald test for each
term in a model fit by svyglm().

I hope this helps,
 John
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of Diana Marcela Martinez Ruiz
Sent: August-02-12 4:14 PM
To: Ayuda en R; tlumley at uw.edu
Subject: [R] summary(svyglm) Pr (> | t |) ?

Hello

I want to know if the summary of the logistic model with survey  Pr (> | t
|) to
test if the coefficient of the model is significant,  ie is the p_valor
wald test
for the model coefficients,  for I am interested to know if the three
levels of
the variable educational level are significant to the model (significance
of
handling 0.2), I present below the results of my model

 summary(mod.logis)

Call:
svyglm(formula = APES_DICOT ~ Nivel_Educativo + Ocupacion_principal +
    Afiliacion_salud + Tiene_cuidador + Presencia_enfer_cronica +
    Consumo_tabaco + Consumo_alcohol + Presencia_Dolor +
Frec_dolor_cronico +
    Punt_min_mental + ABC_fis + ABC_instr + Anergia +
Actividad_fisica_ultimo_aqo +
    Perdida_peso_no_intensionada + Lenta_velocidad_marcha +
Disminucion_fuerza_agarre +
    Hospitalizacion_ultimo_aqo + Urgencias_ultimo_aqo + Miedo_caer,
    design = Muestra.comp, family = quasibinomial())

Survey design:
svydesign(id = ~b, strata = ~d, nest = TRUE, weights = ~c, data = am18,
    fpc = ~e)

Coefficients:
                                        Estimate Std. Error t value
Pr(>|t|)
(Intercept)                             -3.10084    1.85632  -1.670
0.1104
Nivel_EducativoNinguno/No recuerda       1.52556    0.88735   1.719
0.1010
Nivel_EducativoPrimaria                  1.16256    0.64404   1.805
0.0861 .
Nivel_EducativoSecundaria                0.55771    1.04909   0.532
0.6009
Thanks
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Dear Diana,
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of Diana Marcela Martinez Ruiz
Sent: August-02-12 5:00 PM
To: jfox at mcmaster.ca; tlumley at uw.edu; Ayuda en R
Subject: Re: [R] summary(svyglm) Pr (> | t |) ?

Thanks for the info, but with the anova () is obtained  p_valor of Wald
test for

 The standard anova() provides sequential ("type I") tests; by default,
Anova() in car provides partial ("type II") tests.
the variable level of education, I want to see the nievel p_valor in view
of this
variable as a dummy, so I wonder if in summary (mod. logis) the Pr (> | t
|)
lets me know if each level is significant in the model
This is no different for svyglm() than for any model in R with a linear
predictor; the individual t-tests are for (partial) differences between each
other level and the reference level for the set of contrasts (dummy
regressors); if this is what you're interested in (and of course the
reference level isn't arbitrarily chosen), then you can use the t-tests for
the coefficients.

Best,
 John

Thanks

From: jfox at mcmaster.ca
To: dianammr06 at hotmail.com
CC: r-help at r-project.org; tlumley at uw.edu
Subject: RE: [R] summary(svyglm)  Pr (> | t |) ?
Date: Thu, 2 Aug 2012 16:50:37 -0400

Dear Diana,

The Anova() function in the car package will produce a Wald test for
each term in a model fit by svyglm().

I hope this helps,
 John

-----Original Message-----
From: r-help-bounces at r-project.org
[mailto:r-help-bounces at r-project.org]
On Behalf Of Diana Marcela Martinez Ruiz
Sent: August-02-12 4:14 PM
To: Ayuda en R; tlumley at uw.edu
Subject: [R] summary(svyglm) Pr (> | t |) ?

Hello

I want to know if the summary of the logistic model with survey  Pr
(> | t
|) to
test if the coefficient of the model is significant,  ie is the
p_valor
wald test
for the model coefficients,  for I am interested to know if the
three
levels of
the variable educational level are significant to the model
(significance
of
handling 0.2), I present below the results of my model

 summary(mod.logis)

Call:
svyglm(formula = APES_DICOT ~ Nivel_Educativo + Ocupacion_principal +
    Afiliacion_salud + Tiene_cuidador + Presencia_enfer_cronica +
    Consumo_tabaco + Consumo_alcohol + Presencia_Dolor +
Frec_dolor_cronico +
    Punt_min_mental + ABC_fis + ABC_instr + Anergia +
Actividad_fisica_ultimo_aqo +
    Perdida_peso_no_intensionada + Lenta_velocidad_marcha +
Disminucion_fuerza_agarre +
    Hospitalizacion_ultimo_aqo + Urgencias_ultimo_aqo + Miedo_caer,
    design = Muestra.comp, family = quasibinomial())

Survey design:
svydesign(id = ~b, strata = ~d, nest = TRUE, weights = ~c, data =
am18,
    fpc = ~e)

Coefficients:
                                        Estimate Std. Error t value
Pr(>|t|)
(Intercept)                             -3.10084    1.85632  -1.670
0.1104
Nivel_EducativoNinguno/No recuerda       1.52556    0.88735   1.719
0.1010
Nivel_EducativoPrimaria                  1.16256    0.64404   1.805
0.0861 .
Nivel_EducativoSecundaria                0.55771    1.04909   0.532
0.6009
Thanks
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