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dstanley4 / apaTables

Development version of apaTables R package. Current stable version is on the CRAN.
http://dstanley4.github.io/apaTables/
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apa.reg.table_issue with displaying of beta #42

Open jsbyn opened 3 months ago

jsbyn commented 3 months ago

Hello

I am currently stuck with creating an apa-reg-table. Usually, there are columns for beta in the output. However, these columns do not appear in my output (i.e., I only have the columns b/b 95% CI/sr2/sr2 95% CI/Fit/Difference). All of my variables (i.e., predictor variables, interaction term and outcome variable) are numeric. I highly appreciate any help. Thank you!

dstanley4 commented 3 months ago

Can you use a glimpse() command on your data to confirm none of the variables are factors? On May 16, 2024 at 12:11 PM -0400, jsbyn @.***>, wrote:

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Hello

I am currently stuck with creating an apa-reg-table. Usually, there are columns for beta in the output. However, these columns do not appear in my output (i.e., I only have the columns b/b 95% CI/sr2/sr2 95% CI/Fit/Difference). All of my variables (i.e., predictor variables, interaction term and outcome variable) are numeric. I highly appreciate any help. Thank you!

— Reply to this email directly, view it on GitHubhttps://github.com/dstanley4/apaTables/issues/42, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AADGFZRBGVFVKL6JRTZLYHTZCTLDXAVCNFSM6AAAAABH2RCCJKVHI2DSMVQWIX3LMV43ASLTON2WKOZSGMYDAOBRGA4DCOI. You are receiving this because you are subscribed to this thread.Message ID: @.***>

jsbyn commented 3 months ago 
glimpse(mydata)
Rows: 110
Columns: 40
$ tn_code             <chr> "C10J115", "M03A047", "E11P088", "R03G064", "C03M047", "J04B036", "G10M018", "M04T091", "V09M048", "A01W105", "S12F…
$ mean_de_xfinal    <dbl> 3.500, 4.125, 4.500, 4.000, 4.500, 4.000, 4.000, 4.500, 4.500, 4.375, 4.375, 4.375, 4.250, 4.125, 3.875, 3.500, 4.0…
$ mean_de_yfinal    <dbl> 3.125, 3.625, 3.750, 3.500, 4.250, 3.625, 4.000, 4.125, 4.500, 4.125, 3.875, 1.625, 3.250, 3.500, 4.000, 4.000, 3.6…
$ mean_fk_x       <dbl> 5.25, 6.00, 6.00, 5.75, 5.75, 5.75, 4.75, 4.50, 4.25, 6.00, 5.25, 7.00, 6.00, 4.00, 7.00, 5.25, 6.00, 5.75, 6.25, 7…
$ mean_fk_y       <dbl> 5.25, 6.00, 6.00, 5.75, 5.75, 6.00, 4.25, 4.75, 5.00, 6.00, 4.75, 7.00, 6.00, 5.00, 4.25, 4.50, 6.00, 5.25, 6.25, 7…
$ mean_tn_himx   <dbl> 2.666667, 2.666667, 4.000000, 3.666667, 5.000000, 4.000000, 4.000000, 3.333333, 4.666667, 4.333333, 4.666667, 3.000…
$ mean_tn_y   <dbl> 3.666667, 3.000000, 3.666667, 3.000000, 3.666667, 4.000000, 3.666667, 3.333333, 3.666667, 4.000000, 2.666667, 2.000…

And this is the code I am using to (a) calculate the regression analyses and (b) create the apa-reg-table

#(1) model without interaction
reg_yint_yfk_himy <- lm(mean_fk_y ~mean_de_yfinal + mean_tn_y, data = mydata)

#(2) model with interaction
mod_yint_yfk_himy <- lm(mean_fk_y ~mean_de_yfinal * mean_tn_y, data = mydata)

apa.reg.table(reg_yint_yfk_himy , mod_yint_yfk_himy ,filename="RegModTable.doc")

What is even more confusing: When I do not include the interaction term in the model, then I get the "beta" columns in my output.

Thank you !

florgiulianimdq commented 1 week ago

Hi! I have the same problem, were you able to fix it?

dstanley4 commented 1 week ago

As per the documentation you need to use I() around the product term: blk1 <- lm(sales ~ adverts + airplay + I(adverts * airplay), data=album)

florgiulianimdq commented 1 week ago

Thanks! I do not have and interaction term.

lm_1 <- lm(delta_ryff ~ Edad + Genero + Nivel + Rol , base) lm_2 <- lm(delta_ryff ~ Edad + Genero + Nivel + Rol + responsabilidad + extraversion + agradabilidad + neuroticismo + apertura, base)

lm_3 <-lm( delta_ryff ~ Edad + Genero + Nivel + Rol + responsabilidad + extraversion + agradabilidad + neuroticismo + apertura + delta_Cansancio + delta_STAI + delta_Estres, base)

lm_4 <- lm(delta_ryff ~ Edad + Genero + Nivel + Rol + responsabilidad + extraversion + agradabilidad + neuroticismo + apertura + delta_AEF + delta_mait + delta_Cansancio + delta_STAI + delta_Estres + delta_ffmq + delta_scs + delta_Prosoc + delta_AEF + delta_mait + delta_Mindset, base)

apa.reg.table(lm_1,lm_2, lm_3, lm_4, filename="exInteraction1.doc")

dstanley4 commented 1 week ago

Perhaps the underscore in your variable names is causing a problem. This was previously an issue - but I thought it was fixed. Try renaming your variable to see if removing the underscore in your variable names fixes the problem. If so - please let me know. Cheers, David

David Stanley, PhD | Associate Professor Department of Psychology | University of Guelph 50 Stone Rd E | Guelph, ON | N1G 2W1 @. On Aug 27, 2024 at 9:40 AM -0400, florgiulianimdq @.>, wrote:

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Thanks! I do not have and interaction term.

lm_1 <- lm(delta_ryff ~ Edad + Genero + Nivel + Rol , base) lm_2 <- lm(delta_ryff ~ Edad + Genero + Nivel + Rol + responsabilidad + extraversion + agradabilidad + neuroticismo + apertura, base)

lm_3 <-lm( delta_ryff ~ Edad + Genero + Nivel + Rol + responsabilidad + extraversion + agradabilidad + neuroticismo + apertura + delta_Cansancio + delta_STAI + delta_Estres, base)

lm_4 <- lm(delta_ryff ~ Edad + Genero + Nivel + Rol + responsabilidad + extraversion + agradabilidad + neuroticismo + apertura + delta_AEF + delta_mait + delta_Cansancio + delta_STAI + delta_Estres + delta_ffmq + delta_scs + delta_Prosoc + delta_AEF + delta_mait + delta_Mindset, base)

apa.reg.table(lm_1,lm_2, lm_3, lm_4, filename="exInteraction1.doc")

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florgiulianimdq commented 1 week ago

Thank you so much! I´ll try and let you know!

florgiulianimdq commented 1 week ago

It didn't chage, here is the output egression results using deltaryff as the criterion

         Predictor       b        b_95%_CI sr2  sr2_95%_CI             Fit        Difference
       (Intercept)   -2.38  [-13.92, 9.15]                                                  
              Edad    0.16   [-0.11, 0.43] .01 [-.02, .03]                                  
   GeneroMasculino   -5.66  [-12.59, 1.27] .01 [-.02, .05]

NivelNivel primario 5.68* [0.87, 10.50] .03 [-.02, .08]
NivelNivel secundario 1.63 [-3.91, 7.17] .00 [-.01, .01]
NivelNivel superior 13.08 [3.71, 22.45] .04 [-.02, .10]
RolEquipo Directivo 3.43 [-1.80, 8.65] .01 [-.02, .04]
R2 = .118
95% CI[.02,.19] 

       (Intercept)  -17.56  [-44.42, 9.29]                                                  
              Edad    0.16   [-0.11, 0.44] .01 [-.02, .03]                                  
   GeneroMasculino   -5.17  [-12.31, 1.97] .01 [-.02, .04]

NivelNivel primario 5.68* [0.75, 10.61] .03 [-.02, .08]
NivelNivel secundario 2.01 [-3.68, 7.71] .00 [-.01, .02]
NivelNivel superior 13.86* [4.37, 23.34] .05 [-.01, .11]
RolEquipo Directivo 2.87 [-2.42, 8.17] .01 [-.02, .03]
responsabilidad 0.20 [-5.75, 6.14] .00 [-.00, .00]
extraversion 1.68 [-2.42, 5.78] .00 [-.01, .02]
agradabilidad 0.60 [-4.89, 6.10] .00 [-.00, .00]
neuroticismo -0.34 [-4.26, 3.57] .00 [-.00, .00]
apertura 1.80 [-3.18, 6.78] .00 [-.01, .02]
R2 = .138 Delta R2 = .020 95% CI[.00,.18] 95% CI[-.02, .06]

       (Intercept)   -5.60 [-30.82, 19.63]                                                  
              Edad    0.13   [-0.12, 0.39] .01 [-.01, .02]                                  
   GeneroMasculino   -2.77   [-9.43, 3.89] .00 [-.01, .02]

NivelNivel primario 5.35 [0.72, 9.98] .03 [-.02, .07]
NivelNivel secundario 2.54 [-2.73, 7.80] .00 [-.01, .02]
NivelNivel superior 9.45 [0.47, 18.43] .02 [-.02, .06]
RolEquipo Directivo 3.65 [-1.28, 8.59] .01 [-.02, .04]
responsabilidad -3.24 [-8.90, 2.43] .01 [-.01, .03]
extraversion 1.70 [-2.10, 5.50] .00 [-.01, .02]
agradabilidad 2.60 [-2.53, 7.73] .00 [-.01, .02]
neuroticismo -0.56 [-4.20, 3.08] .00 [-.01, .01]
apertura 0.16 [-4.52, 4.84] .00 [-.00, .00]
deltaCansancio -0.01 [-0.25, 0.24] .00 [-.00, .00]
deltaSTAI -0.44 [-0.76, -0.11] .03 [-.01, .08]
deltaEstres -0.63 [-0.95, -0.31] .07 [.01, .14]
R2 = .279 Delta R2 = .141 95% CI[.10,.33] 95% CI[.05, .23]

       (Intercept)  -10.93 [-36.23, 14.36]                                                  
              Edad    0.08   [-0.18, 0.34] .00 [-.01, .01]                                  
   GeneroMasculino   -2.39   [-9.01, 4.24] .00 [-.01, .01]

NivelNivel primario 5.77* [1.13, 10.41] .03 [-.01, .07]
NivelNivel secundario 2.21 [-3.04, 7.46] .00 [-.01, .02]
NivelNivel superior 6.14 [-2.90, 15.17] .01 [-.01, .03]
RolEquipo Directivo 3.88 [-0.95, 8.71] .01 [-.01, .04]
responsabilidad -3.76 [-9.33, 1.82] .01 [-.01, .03]
extraversion 2.09 [-1.71, 5.89] .01 [-.01, .02]
agradabilidad 3.92 [-1.23, 9.07] .01 [-.01, .04]
neuroticismo 0.23 [-3.42, 3.89] .00 [-.00, .00]
apertura 0.26 [-4.32, 4.84] .00 [-.00, .00]
deltaCansancio 0.02 [-0.23, 0.27] .00 [-.00, .00]
deltaSTAI -0.31 [-0.65, 0.02] .02 [-.02, .05]
deltaEstres -0.53 [-0.86, -0.21] .05 [-.01, .10]
deltaffmq 0.15 [0.00, 0.29] .02 [-.01, .05]
deltascs 0.17 [-0.21, 0.55] .00 [-.01, .02]
deltaProsoc 0.27 [0.03, 0.51] .02 [-.01, .06]
deltaAEF 0.02 [-0.42, 0.46] .00 [-.00, .00]
deltamait 0.71 [-0.89, 2.31] .00 [-.01, .02]
deltaMindset -0.07 [-0.60, 0.46] .00 [-.00, .00]
R2 = .349 Delta R2 = .070* 95% CI[.14,.38] 95% CI[.01, .13]

Note. A significant b-weight indicates the semi-partial correlation is also significant. b represents unstandardized regression weights. sr2 represents the semi-partial correlation squared. Square brackets are used to enclose the lower and upper limits of a confidence interval.