Ruby - ACIRI
Luis Anunciacao
27 February, 2019
Function – Linear model
lm_results <- function(dv, iv) {
#Constrastes para Anova
#options("contrasts")
options(contrasts = c("contr.helmert", "contr.poly")) #all the time we need this option
#Do Regression analysis
mod <- eval(substitute(lm(dv ~ iv + ChildsAge + relevel(Condition,ref = 2), data = dataset)))
#display results
print(anova_stats(car::Anova(mod, type = 3)))
#constrastes para regressao
options(contrasts = c("contr.treatment", "contr.poly")) #all the time we need this option
mod2 <- eval(substitute(lm(dv ~ iv + ChildsAge + relevel(Condition,ref = 2), data = dataset)))
#glance(mod2)
summary(mod2)
}Factor 1 - Child interest in literacy
## term sumsq meansq df statistic p.value etasq
## 1 (Intercept) 0.735 0.735 1 2.524 0.136 0.078
## 2 child_interest_total_t1 3.843 3.843 1 13.200 0.003 0.407
## 3 ChildsAge 0.024 0.024 1 0.081 0.781 0.002
## 4 relevel(Condition, ref = 2) 1.063 1.063 1 3.652 0.078 0.113
## 5 Residuals 3.785 0.291 13 NA NA NA
## partial.etasq omegasq partial.omegasq cohens.f power
## 1 0.163 0.046 0.078 0.441 0.353
## 2 0.504 0.365 0.404 1.008 0.950
## 3 0.006 -0.027 -0.054 0.079 0.059
## 4 0.219 0.079 0.128 0.530 0.476
## 5 NA NA NA NA NA##
## Call:
## lm(formula = child_interest_total_t2 ~ child_interest_total_t1 +
## ChildsAge + relevel(Condition, ref = 2), data = dataset)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.722 -0.413 -0.006 0.356 0.794
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.17119 0.89833 1.30 0.215
## child_interest_total_t1 0.74720 0.20566 3.63 0.003 **
## ChildsAge -0.00786 0.02766 -0.28 0.781
## relevel(Condition, ref = 2)1 0.51391 0.26891 1.91 0.078 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.54 on 13 degrees of freedom
## Multiple R-squared: 0.604, Adjusted R-squared: 0.513
## F-statistic: 6.62 on 3 and 13 DF, p-value: 0.00593## Some items ( T1SingSongs T1ListenMusic ) were negatively correlated with the total scale and
## probably should be reversed.
## To do this, run the function again with the 'check.keys=TRUE' option##
## Reliability analysis
## Call: alpha(x = .)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
## 0.65 0.63 0.76 0.16 1.7 0.11 4.8 0.75 0.11
##
## lower alpha upper 95% confidence boundaries
## 0.44 0.65 0.85
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se
## T1SingSongs 0.67 0.68 0.77 0.21 2.1 0.102
## T1IndependentColoring 0.59 0.52 0.64 0.12 1.1 0.122
## T1PretendWrite 0.60 0.52 0.68 0.12 1.1 0.118
## T1ListenMusic 0.68 0.69 0.77 0.22 2.3 0.098
## T1TellStory 0.54 0.55 0.66 0.13 1.2 0.146
## T1Lookmagazine 0.60 0.59 0.74 0.15 1.4 0.119
## T1LookNewspaper 0.63 0.61 0.76 0.17 1.6 0.104
## T1DoCard 0.57 0.58 0.73 0.15 1.4 0.129
## T1IndependentBook 0.64 0.60 0.73 0.16 1.5 0.108
## var.r med.r
## T1SingSongs 0.069 0.216
## T1IndependentColoring 0.046 0.101
## T1PretendWrite 0.055 0.092
## T1ListenMusic 0.059 0.216
## T1TellStory 0.057 0.101
## T1Lookmagazine 0.078 0.101
## T1LookNewspaper 0.083 0.177
## T1DoCard 0.072 0.092
## T1IndependentBook 0.072 0.101
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## T1SingSongs 17 0.104 0.19 0.034 -0.014 6.5 0.80
## T1IndependentColoring 17 0.673 0.74 0.806 0.591 6.2 0.88
## T1PretendWrite 17 0.628 0.74 0.774 0.545 6.1 0.83
## T1ListenMusic 17 -0.089 0.11 -0.022 -0.180 6.5 0.62
## T1TellStory 17 0.786 0.67 0.685 0.574 4.4 2.37
## T1Lookmagazine 17 0.669 0.54 0.431 0.423 2.9 2.18
## T1LookNewspaper 17 0.473 0.46 0.320 0.272 1.8 1.51
## T1DoCard 17 0.685 0.58 0.498 0.490 2.2 1.86
## T1IndependentBook 17 0.362 0.49 0.414 0.253 6.4 0.80
##
## Non missing response frequency for each item
## 1 2 3 4 5 6 7 miss
## T1SingSongs 0.00 0.00 0.00 0.00 0.18 0.12 0.71 0
## T1IndependentColoring 0.00 0.00 0.00 0.06 0.12 0.41 0.41 0
## T1PretendWrite 0.00 0.00 0.00 0.06 0.12 0.53 0.29 0
## T1ListenMusic 0.00 0.00 0.00 0.00 0.06 0.41 0.53 0
## T1TellStory 0.29 0.00 0.00 0.06 0.12 0.41 0.12 0
## T1Lookmagazine 0.47 0.06 0.12 0.06 0.12 0.12 0.06 0
## T1LookNewspaper 0.65 0.18 0.06 0.00 0.06 0.06 0.00 0
## T1DoCard 0.59 0.12 0.00 0.18 0.06 0.00 0.06 0
## T1IndependentBook 0.00 0.00 0.00 0.06 0.00 0.41 0.53 0Factor 2 - Adults value placed on literacy
## term sumsq meansq df statistic p.value etasq
## 1 (Intercept) 1.55 1.55 1 1.97 0.184 0.094
## 2 adults_literacy_total_t1 3.44 3.44 1 4.35 0.057 0.209
## 3 ChildsAge 0.36 0.36 1 0.45 0.514 0.022
## 4 relevel(Condition, ref = 2) 0.86 0.86 1 1.08 0.317 0.052
## 5 Residuals 10.29 0.79 13 NA NA NA
## partial.etasq omegasq partial.omegasq cohens.f power
## 1 0.131 0.044 0.051 0.39 0.29
## 2 0.251 0.153 0.157 0.58 0.54
## 3 0.033 -0.025 -0.032 0.19 0.10
## 4 0.077 0.004 0.005 0.29 0.18
## 5 NA NA NA NA NA##
## Call:
## lm(formula = adults_literacy_total_t2 ~ adults_literacy_total_t1 +
## ChildsAge + relevel(Condition, ref = 2), data = dataset)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.2520 -0.7447 0.0027 0.3269 2.0061
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.3998 1.2123 1.15 0.269
## adults_literacy_total_t1 0.4530 0.2171 2.09 0.057 .
## ChildsAge 0.0276 0.0412 0.67 0.514
## relevel(Condition, ref = 2)1 0.5053 0.4855 1.04 0.317
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.89 on 13 degrees of freedom
## Multiple R-squared: 0.316, Adjusted R-squared: 0.158
## F-statistic: 2 on 3 and 13 DF, p-value: 0.164##
## Reliability analysis
## Call: alpha(x = ., check.keys = T)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
## 0.82 0.82 0.95 0.28 4.6 0.06 3.8 1.2 0.27
##
## lower alpha upper 95% confidence boundaries
## 0.71 0.82 0.94
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se
## SendTextMsg 0.82 0.82 0.95 0.29 4.5 0.062
## WriteEmails 0.80 0.80 0.94 0.27 4.0 0.068
## ReadOnline 0.82 0.82 0.94 0.29 4.4 0.063
## LeaveWrittenMessage 0.80 0.80 0.91 0.27 4.0 0.068
## ToBuyOrDoList 0.79 0.79 0.93 0.26 3.8 0.071
## ReadMagazine 0.82 0.82 0.94 0.29 4.5 0.060
## ReadNewspaper 0.82 0.81 0.92 0.28 4.2 0.063
## ReadBookNovel- 0.85 0.84 0.94 0.33 5.4 0.054
## UseDictionary 0.81 0.81 0.93 0.28 4.2 0.063
## ReadAdvertisements 0.80 0.80 0.92 0.26 3.9 0.070
## UseCookBook 0.79 0.79 0.94 0.25 3.7 0.074
## ReadBible 0.80 0.80 0.91 0.26 3.9 0.069
## var.r med.r
## SendTextMsg 0.057 0.28
## WriteEmails 0.055 0.27
## ReadOnline 0.058 0.31
## LeaveWrittenMessage 0.048 0.26
## ToBuyOrDoList 0.056 0.24
## ReadMagazine 0.049 0.29
## ReadNewspaper 0.048 0.29
## ReadBookNovel- 0.036 0.31
## UseDictionary 0.049 0.27
## ReadAdvertisements 0.054 0.26
## UseCookBook 0.047 0.26
## ReadBible 0.051 0.27
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## SendTextMsg 17 0.46 0.47 0.40 0.364 5.7 1.8
## WriteEmails 16 0.68 0.65 0.62 0.560 3.9 2.5
## ReadOnline 17 0.52 0.51 0.48 0.404 6.1 1.7
## LeaveWrittenMessage 17 0.66 0.66 0.66 0.575 2.8 1.8
## ToBuyOrDoList 17 0.74 0.73 0.71 0.662 4.1 2.3
## ReadMagazine 17 0.43 0.48 0.46 0.326 2.8 1.7
## ReadNewspaper 16 0.51 0.58 0.58 0.428 2.3 1.7
## ReadBookNovel- 17 0.18 0.16 0.12 0.039 3.6 2.0
## UseDictionary 17 0.53 0.58 0.57 0.443 2.3 1.5
## ReadAdvertisements 17 0.72 0.69 0.69 0.622 4.4 2.2
## UseCookBook 17 0.79 0.77 0.76 0.718 3.8 2.2
## ReadBible 16 0.76 0.70 0.71 0.622 3.3 1.9
##
## Non missing response frequency for each item
## 1 2 3 4 5 6 7 miss
## SendTextMsg 0.06 0.00 0.06 0.12 0.12 0.12 0.53 0.00
## WriteEmails 0.25 0.19 0.06 0.06 0.00 0.19 0.25 0.06
## ReadOnline 0.06 0.00 0.06 0.00 0.00 0.29 0.59 0.00
## LeaveWrittenMessage 0.35 0.06 0.35 0.06 0.06 0.06 0.06 0.00
## ToBuyOrDoList 0.29 0.00 0.06 0.18 0.06 0.29 0.12 0.00
## ReadMagazine 0.35 0.18 0.06 0.24 0.12 0.06 0.00 0.00
## ReadNewspaper 0.56 0.06 0.00 0.25 0.12 0.00 0.00 0.06
## ReadBookNovel 0.06 0.24 0.12 0.06 0.00 0.47 0.06 0.00
## UseDictionary 0.41 0.24 0.18 0.06 0.06 0.06 0.00 0.00
## ReadAdvertisements 0.24 0.00 0.06 0.18 0.12 0.24 0.18 0.00
## UseCookBook 0.29 0.06 0.00 0.24 0.18 0.12 0.12 0.00
## ReadBible 0.25 0.19 0.00 0.31 0.06 0.19 0.00 0.06Factor 3 - Press for achievement
## term sumsq meansq df statistic p.value etasq
## 1 (Intercept) 3.683 3.683 1 5.249 0.039 0.131
## 2 press4achievement_total_t1 14.069 14.069 1 20.052 0.001 0.502
## 3 ChildsAge 1.178 1.178 1 1.679 0.218 0.042
## 4 relevel(Condition, ref = 2) 0.002 0.002 1 0.002 0.964 0.000
## 5 Residuals 9.121 0.702 13 NA NA NA
## partial.etasq omegasq partial.omegasq cohens.f power
## 1 0.29 0.104 0.191 0.635 0.62
## 2 0.61 0.465 0.514 1.242 0.99
## 3 0.11 0.017 0.036 0.359 0.25
## 4 0.00 -0.024 -0.059 0.013 0.05
## 5 NA NA NA NA NA##
## Call:
## lm(formula = press4achievement_total_t2 ~ press4achievement_total_t1 +
## ChildsAge + relevel(Condition, ref = 2), data = dataset)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.5473 -0.3785 0.0877 0.6129 1.0905
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.4034 1.0325 2.33 0.03672 *
## press4achievement_total_t1 0.8448 0.1887 4.48 0.00062 ***
## ChildsAge -0.0546 0.0421 -1.30 0.21764
## relevel(Condition, ref = 2)1 -0.0195 0.4177 -0.05 0.96351
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.84 on 13 degrees of freedom
## Multiple R-squared: 0.615, Adjusted R-squared: 0.527
## F-statistic: 6.93 on 3 and 13 DF, p-value: 0.00498##
## Reliability analysis
## Call: alpha(x = .)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
## 0.76 0.76 0.83 0.34 3.1 0.089 4.6 1.2 0.38
##
## lower alpha upper 95% confidence boundaries
## 0.59 0.76 0.93
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se
## TalkSoundsLetters 0.75 0.74 0.81 0.36 2.8 0.089
## TalkAlphabet 0.75 0.75 0.82 0.38 3.0 0.096
## ReadSignboardWChild 0.64 0.64 0.72 0.26 1.8 0.141
## HelpChildWrite 0.66 0.67 0.72 0.29 2.0 0.126
## PrintedInstructGame 0.78 0.78 0.81 0.41 3.5 0.083
## TakeChildLibrary 0.73 0.72 0.81 0.34 2.6 0.099
## var.r med.r
## TalkSoundsLetters 0.067 0.40
## TalkAlphabet 0.079 0.41
## ReadSignboardWChild 0.063 0.32
## HelpChildWrite 0.056 0.38
## PrintedInstructGame 0.029 0.38
## TakeChildLibrary 0.073 0.37
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## TalkSoundsLetters 17 0.63 0.62 0.52 0.41 4.6 2.1
## TalkAlphabet 17 0.52 0.58 0.47 0.38 5.8 1.2
## ReadSignboardWChild 17 0.88 0.87 0.88 0.78 4.6 2.1
## HelpChildWrite 17 0.82 0.80 0.81 0.71 4.5 2.0
## PrintedInstructGame 16 0.50 0.50 0.42 0.29 5.4 1.9
## TakeChildLibrary 17 0.66 0.66 0.56 0.48 2.8 1.8
##
## Non missing response frequency for each item
## 1 2 3 4 5 6 7 miss
## TalkSoundsLetters 0.18 0.00 0.06 0.18 0.12 0.29 0.18 0.00
## TalkAlphabet 0.00 0.00 0.06 0.12 0.12 0.35 0.35 0.00
## ReadSignboardWChild 0.12 0.12 0.06 0.06 0.24 0.24 0.18 0.00
## HelpChildWrite 0.18 0.00 0.06 0.18 0.24 0.24 0.12 0.00
## PrintedInstructGame 0.06 0.06 0.06 0.00 0.12 0.38 0.31 0.06
## TakeChildLibrary 0.35 0.18 0.12 0.18 0.06 0.12 0.00 0.00Factor 4 - Attitude toward reading
## term sumsq meansq df statistic p.value etasq
## 1 (Intercept) 0.001 0.001 1 0.011 0.92 0.000
## 2 attitude_factor1_t1 4.973 4.973 1 58.700 0.00 0.787
## 3 ChildsAge 0.002 0.002 1 0.020 0.89 0.000
## 4 relevel(Condition, ref = 2) 0.242 0.242 1 2.856 0.12 0.038
## 5 Residuals 1.101 0.085 13 NA NA NA
## partial.etasq omegasq partial.omegasq cohens.f power
## 1 0.001 -0.013 -0.058 0.029 0.051
## 2 0.819 0.763 0.762 2.125 1.000
## 3 0.001 -0.013 -0.058 0.039 0.052
## 4 0.180 0.025 0.093 0.469 0.390
## 5 NA NA NA NA NA##
## Call:
## lm(formula = attitude_factor1_t2 ~ attitude_factor1_t1 + ChildsAge +
## relevel(Condition, ref = 2), data = dataset)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.3631 -0.2117 -0.0473 0.1772 0.5009
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.16258 0.37141 0.44 0.67
## attitude_factor1_t1 0.86462 0.11285 7.66 3.6e-06 ***
## ChildsAge 0.00184 0.01316 0.14 0.89
## relevel(Condition, ref = 2)1 -0.24856 0.14708 -1.69 0.11
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.29 on 13 degrees of freedom
## Multiple R-squared: 0.841, Adjusted R-squared: 0.805
## F-statistic: 23 on 3 and 13 DF, p-value: 0.0000179## term sumsq meansq df statistic p.value etasq
## 1 (Intercept) 3.559 3.559 1 64.6 0.000 0.744
## 2 attitude_factor2_t1 0.049 0.049 1 0.9 0.361 0.010
## 3 ChildsAge 0.082 0.082 1 1.5 0.243 0.017
## 4 relevel(Condition, ref = 2) 0.378 0.378 1 6.9 0.021 0.079
## 5 Residuals 0.716 0.055 13 NA NA NA
## partial.etasq omegasq partial.omegasq cohens.f power
## 1 0.833 0.724 0.779 2.23 1.00
## 2 0.065 -0.001 -0.006 0.26 0.16
## 3 0.103 0.006 0.027 0.34 0.23
## 4 0.345 0.067 0.246 0.73 0.74
## 5 NA NA NA NA NA##
## Call:
## lm(formula = attitude_factor2_t2 ~ attitude_factor2_t1 + ChildsAge +
## relevel(Condition, ref = 2), data = dataset)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.5826 -0.0833 0.0328 0.1412 0.2644
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.7286 0.3529 7.73 3.2e-06 ***
## attitude_factor2_t1 0.1034 0.1092 0.95 0.361
## ChildsAge 0.0142 0.0116 1.22 0.243
## relevel(Condition, ref = 2)1 0.3052 0.1165 2.62 0.021 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.23 on 13 degrees of freedom
## Multiple R-squared: 0.509, Adjusted R-squared: 0.396
## F-statistic: 4.5 on 3 and 13 DF, p-value: 0.0225## term sumsq meansq df statistic p.value etasq
## 1 (Intercept) 0.077 0.077 1 1.078 0.318 0.035
## 2 attitude_total_t1 1.179 1.179 1 16.440 0.001 0.533
## 3 ChildsAge 0.022 0.022 1 0.305 0.590 0.010
## 4 relevel(Condition, ref = 2) 0.003 0.003 1 0.036 0.852 0.001
## 5 Residuals 0.932 0.072 13 NA NA NA
## partial.etasq omegasq partial.omegasq cohens.f power
## 1 0.077 0.002 0.004 0.288 0.179
## 2 0.558 0.485 0.462 1.125 0.980
## 3 0.023 -0.022 -0.040 0.153 0.085
## 4 0.003 -0.030 -0.057 0.053 0.054
## 5 NA NA NA NA NA##
## Call:
## lm(formula = attitude_total_t2 ~ attitude_total_t1 + ChildsAge +
## relevel(Condition, ref = 2), data = dataset)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.3478 -0.1609 -0.0405 0.1177 0.5234
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.51004 0.48798 1.05 0.3150
## attitude_total_t1 0.87143 0.21492 4.05 0.0014 **
## ChildsAge -0.00729 0.01321 -0.55 0.5902
## relevel(Condition, ref = 2)1 -0.02614 0.13750 -0.19 0.8522
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.27 on 13 degrees of freedom
## Multiple R-squared: 0.594, Adjusted R-squared: 0.501
## F-statistic: 6.35 on 3 and 13 DF, p-value: 0.00695##
## Reliability analysis
## Call: alpha(x = ., check.keys = TRUE)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
## 0.86 0.86 1 0.33 6.4 0.05 1.7 0.56 0.34
##
## lower alpha upper 95% confidence boundaries
## 0.76 0.86 0.96
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc)
## CantReadChildNoSpaceT1 0.84 0.84 1
## DontHaveMatT1 0.85 0.85 1
## CantReadChildMoreImportantThingsToDoT1 0.83 0.84 1
## CantReadChildMovesTooMuchT1 0.86 0.86 1
## DifficultBoringReadChildT1 0.85 0.86 1
## DisciplineWhenReadingt1 0.84 0.84 1
## TooBusyTiredReadChildT1 0.84 0.84 1
## CannotReadSoCantReadChildT1 0.85 0.85 1
## WantChildValueBookst1- 0.86 0.87 1
## ChildLikesToBeReadT1- 0.86 0.86 1
## FeelCloseWhenReadingT1- 0.86 0.87 1
## TryToBeEnthusiasticWReadT1- 0.84 0.85 1
## ReadWhenChildWantsT1- 0.87 0.87 1
## average_r S/N alpha se var.r med.r
## CantReadChildNoSpaceT1 0.31 5.3 0.058 0.061 0.31
## DontHaveMatT1 0.32 5.7 0.056 0.068 0.31
## CantReadChildMoreImportantThingsToDoT1 0.30 5.2 0.060 0.065 0.29
## CantReadChildMovesTooMuchT1 0.34 6.2 0.051 0.068 0.35
## DifficultBoringReadChildT1 0.33 6.0 0.053 0.060 0.35
## DisciplineWhenReadingt1 0.31 5.3 0.059 0.069 0.29
## TooBusyTiredReadChildT1 0.31 5.4 0.058 0.071 0.29
## CannotReadSoCantReadChildT1 0.33 5.9 0.054 0.069 0.35
## WantChildValueBookst1- 0.35 6.5 0.049 0.071 0.36
## ChildLikesToBeReadT1- 0.35 6.3 0.051 0.067 0.36
## FeelCloseWhenReadingT1- 0.35 6.4 0.051 0.066 0.35
## TryToBeEnthusiasticWReadT1- 0.32 5.7 0.056 0.074 0.31
## ReadWhenChildWantsT1- 0.36 6.8 0.047 0.063 0.36
##
## Item statistics
## n raw.r std.r r.cor r.drop mean
## CantReadChildNoSpaceT1 16 0.81 0.80 0.80 0.73 1.7
## DontHaveMatT1 17 0.67 0.69 0.69 0.60 1.6
## CantReadChildMoreImportantThingsToDoT1 17 0.83 0.83 0.83 0.76 1.8
## CantReadChildMovesTooMuchT1 16 0.53 0.53 0.53 0.43 1.9
## DifficultBoringReadChildT1 16 0.53 0.58 0.58 0.49 1.4
## DisciplineWhenReadingt1 16 0.79 0.79 0.79 0.76 1.8
## TooBusyTiredReadChildT1 16 0.76 0.76 0.76 0.71 2.2
## CannotReadSoCantReadChildT1 17 0.59 0.62 0.62 0.52 1.5
## WantChildValueBookst1- 17 0.46 0.44 0.44 0.34 1.7
## ChildLikesToBeReadT1- 17 0.49 0.48 0.48 0.39 1.7
## FeelCloseWhenReadingT1- 17 0.47 0.45 0.45 0.37 1.5
## TryToBeEnthusiasticWReadT1- 17 0.71 0.69 0.69 0.62 1.8
## ReadWhenChildWantsT1- 17 0.34 0.36 0.36 0.22 2.0
## sd
## CantReadChildNoSpaceT1 0.87
## DontHaveMatT1 1.00
## CantReadChildMoreImportantThingsToDoT1 1.01
## CantReadChildMovesTooMuchT1 1.06
## DifficultBoringReadChildT1 0.62
## DisciplineWhenReadingt1 0.86
## TooBusyTiredReadChildT1 0.86
## CannotReadSoCantReadChildT1 0.87
## WantChildValueBookst1- 1.05
## ChildLikesToBeReadT1- 0.85
## FeelCloseWhenReadingT1- 0.80
## TryToBeEnthusiasticWReadT1- 1.03
## ReadWhenChildWantsT1- 1.00
##
## Non missing response frequency for each item
## 1 2 3 4 miss
## CantReadChildNoSpaceT1 0.50 0.38 0.06 0.06 0.06
## DontHaveMatT1 0.65 0.24 0.00 0.12 0.00
## CantReadChildMoreImportantThingsToDoT1 0.47 0.35 0.06 0.12 0.00
## CantReadChildMovesTooMuchT1 0.44 0.31 0.12 0.12 0.06
## DifficultBoringReadChildT1 0.69 0.25 0.06 0.00 0.06
## DisciplineWhenReadingt1 0.50 0.25 0.25 0.00 0.06
## TooBusyTiredReadChildT1 0.19 0.44 0.31 0.06 0.06
## CannotReadSoCantReadChildT1 0.65 0.24 0.06 0.06 0.00
## WantChildValueBookst1 0.12 0.06 0.24 0.59 0.00
## ChildLikesToBeReadT1 0.06 0.06 0.41 0.47 0.00
## FeelCloseWhenReadingT1 0.06 0.00 0.35 0.59 0.00
## TryToBeEnthusiasticWReadT1 0.12 0.06 0.29 0.53 0.00
## ReadWhenChildWantsT1 0.12 0.12 0.41 0.35 0.00
## geom_errorbar: na.rm = FALSE
## stat_summary: na.rm = FALSE, fun.data = function (x, mult = 1)
## {
## x <- stats::na.omit(x)
## se <- mult * sqrt(stats::var(x)/length(x))
## mean <- mean(x)
## data.frame(y = mean, ymin = mean - se, ymax = mean + se)
## }
## position_identity## geom_errorbar: na.rm = FALSE, width = 0.2
## stat_summary: fun.data = function (x, ...)
## {
## if (!requireNamespace("Hmisc", quietly = TRUE))
## stop("Hmisc package required for this function", call. = FALSE)
## fun <- getExportedValue("Hmisc", fun)
## result <- do.call(fun, list(x = quote(x), ...))
## plyr::rename(data.frame(t(result)), c(Median = "y", Mean = "y", Lower = "ymin", Upper = "ymax"), warn_missing = FALSE)
## }, fun.y = NULL, fun.ymax = NULL, fun.ymin = NULL, fun.args = list(), na.rm = FALSE
## position_identityFactor 5 - Availability
## term sumsq meansq df statistic p.value etasq
## 1 (Intercept) 0.063 0.063 1 0.074 0.79 0.002
## 2 availability_t1 22.359 22.359 1 26.379 0.00 0.662
## 3 ChildsAge 0.238 0.238 1 0.281 0.60 0.007
## 4 relevel(Condition, ref = 2) 0.077 0.077 1 0.091 0.77 0.002
## 5 Residuals 11.019 0.848 13 NA NA NA
## partial.etasq omegasq partial.omegasq cohens.f power
## 1 0.006 -0.023 -0.054 0.076 0.059
## 2 0.670 0.622 0.585 1.424 0.999
## 3 0.021 -0.018 -0.042 0.147 0.083
## 4 0.007 -0.022 -0.053 0.084 0.060
## 5 NA NA NA NA NA##
## Call:
## lm(formula = availability_t2 ~ availability_t1 + ChildsAge +
## relevel(Condition, ref = 2), data = dataset)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.470 -0.482 -0.213 0.886 1.225
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.2245 1.0505 -0.21 0.83410
## availability_t1 1.1600 0.2259 5.14 0.00019 ***
## ChildsAge 0.0231 0.0435 0.53 0.60478
## relevel(Condition, ref = 2)1 -0.1433 0.4746 -0.30 0.76752
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.92 on 13 degrees of freedom
## Multiple R-squared: 0.723, Adjusted R-squared: 0.659
## F-statistic: 11.3 on 3 and 13 DF, p-value: 0.000631##
## Reliability analysis
## Call: alpha(x = .)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
## 0.02 0.022 0.011 0.011 0.022 0.44 2.4 1.1 0.011
##
## lower alpha upper 95% confidence boundaries
## -0.84 0.02 0.88
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se
## AdultsBooksAtHomeT1 0.01100 0.011 0.00012 0.011 NA NA
## HowManyBooksChildHave 0.00012 0.011 NA NA NA NA
## var.r med.r
## AdultsBooksAtHomeT1 0.01100 0.011
## HowManyBooksChildHave 0.00012 0.011
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## AdultsBooksAtHomeT1 17 0.56 0.71 0.075 0.011 2.2 1.3
## HowManyBooksChildHave 17 0.83 0.71 0.075 0.011 2.6 1.9
##
## Non missing response frequency for each item
## 1 2 3 4 5 6 7 miss
## AdultsBooksAtHomeT1 0.24 0.53 0.12 0.06 0.00 0.06 0.00 0
## HowManyBooksChildHave 0.35 0.24 0.18 0.06 0.06 0.06 0.06 0Factor 6 - Reading
## term sumsq meansq df statistic p.value etasq
## 1 (Intercept) 1.72 1.72 1 3.5 0.084 0.076
## 2 reading_t1 13.76 13.76 1 28.0 0.000 0.613
## 3 ChildsAge 0.00 0.00 1 0.0 0.996 0.000
## 4 relevel(Condition, ref = 2) 0.58 0.58 1 1.2 0.296 0.026
## 5 Residuals 6.38 0.49 13 NA NA NA
## partial.etasq omegasq partial.omegasq cohens.f power
## 1 0.212 0.053 0.122 0.519 0.46
## 2 0.683 0.579 0.600 1.469 1.00
## 3 0.000 -0.021 -0.059 0.002 0.05
## 4 0.084 0.004 0.010 0.302 0.19
## 5 NA NA NA NA NA##
## Call:
## lm(formula = reading_t2 ~ reading_t1 + ChildsAge + relevel(Condition,
## ref = 2), data = dataset)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.335 -0.401 0.353 0.424 0.653
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.844931 1.094667 1.69 0.11575
## reading_t1 0.622474 0.117555 5.30 0.00015 ***
## ChildsAge -0.000182 0.031733 -0.01 0.99551
## relevel(Condition, ref = 2)1 0.383572 0.352080 1.09 0.29574
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7 on 13 degrees of freedom
## Multiple R-squared: 0.687, Adjusted R-squared: 0.615
## F-statistic: 9.51 on 3 and 13 DF, p-value: 0.00137##
## Reliability analysis
## Call: alpha(x = .)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
## 0.66 0.68 0.52 0.52 2.2 0.15 5.4 1.5 0.52
##
## lower alpha upper 95% confidence boundaries
## 0.36 0.66 0.97
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r
## MomReadChild 0.52 0.52 0.27 0.52 NA NA 0.52
## DadReadChild 0.27 0.52 NA NA NA NA 0.27
## med.r
## MomReadChild 0.52
## DadReadChild 0.52
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## MomReadChild 17 0.83 0.87 0.63 0.52 6.1 1.5
## DadReadChild 17 0.91 0.87 0.63 0.52 4.6 2.0
##
## Non missing response frequency for each item
## 1 3 4 5 6 7 miss
## MomReadChild 0.06 0.00 0.00 0.12 0.29 0.53 0
## DadReadChild 0.18 0.06 0.06 0.41 0.12 0.18 0Function for Correlations
corstars <- function(x, method=c("pearson", "spearman"), removeTriangle=c("upper", "lower"),
result=c("none", "html", "latex")) {
#Compute correlation matrix
require(Hmisc)
library(xtable)
x <- as.matrix(x)
correlation_matrix<-rcorr(x, type=method[1])
R <- correlation_matrix$r # Matrix of correlation coeficients
p <- correlation_matrix$P # Matrix of p-value
## Define notions for significance levels; spacing is important.
mystars <- ifelse(p < .0001, "****", ifelse(p < .001, "*** ", ifelse(p < .01, "** ", ifelse(p < .05, "* ", " "))))
## trunctuate the correlation matrix to two decimal
R <- format(round(cbind(rep(-1.11, ncol(x)), R), 2))[,-1]
## build a new matrix that includes the correlations with their apropriate stars
Rnew <- matrix(paste(R, mystars, sep=""), ncol=ncol(x))
diag(Rnew) <- paste(diag(R), " ", sep="")
rownames(Rnew) <- colnames(x)
colnames(Rnew) <- paste(colnames(x), "", sep="")
## remove upper triangle of correlation matrix
if(removeTriangle[1]=="upper"){
Rnew <- as.matrix(Rnew)
Rnew[upper.tri(Rnew, diag = TRUE)] <- ""
Rnew <- as.data.frame(Rnew)
}
## remove lower triangle of correlation matrix
else if(removeTriangle[1]=="lower"){
Rnew <- as.matrix(Rnew)
Rnew[lower.tri(Rnew, diag = TRUE)] <- ""
Rnew <- as.data.frame(Rnew)
}
## remove last column and return the correlation matrix
Rnew <- cbind(Rnew[1:length(Rnew)-1])
if (result[1]=="none") return(Rnew)
else{
if(result[1]=="html") print(xtable(Rnew), type="html")
else print(xtable(Rnew), type="latex")
}
}Bivariate correlation
The previous results was:
## ValueLiteracyMSt1 PressAchievMSt1wLIB
## ValueLiteracyMSt1
## PressAchievMSt1wLIB 0.03
## AvailabilityBooksMSt1 0.27 0.40
## BookReadingWChildMOMDADSt1 0.30 0.47
## AttitudeScaleMSt1 0.55* 0.10
## TOTALACIRICHILDT1 -0.31 0.22
## TOTALACIRIADULTT1 0.01 -0.01
## AvailabilityBooksMSt1
## ValueLiteracyMSt1
## PressAchievMSt1wLIB
## AvailabilityBooksMSt1
## BookReadingWChildMOMDADSt1 0.36
## AttitudeScaleMSt1 0.19
## TOTALACIRICHILDT1 -0.01
## TOTALACIRIADULTT1 0.25
## BookReadingWChildMOMDADSt1 AttitudeScaleMSt1
## ValueLiteracyMSt1
## PressAchievMSt1wLIB
## AvailabilityBooksMSt1
## BookReadingWChildMOMDADSt1
## AttitudeScaleMSt1 0.02
## TOTALACIRICHILDT1 -0.03 -0.16
## TOTALACIRIADULTT1 0.08 0.01
## TOTALACIRICHILDT1
## ValueLiteracyMSt1
## PressAchievMSt1wLIB
## AvailabilityBooksMSt1
## BookReadingWChildMOMDADSt1
## AttitudeScaleMSt1
## TOTALACIRICHILDT1
## TOTALACIRIADULTT1 0.62**And the present result is:
## child_interest_total_t1
## child_interest_total_t1
## adults_literacy_total_t1 0.17
## press4achievement_total_t1 0.63**
## availability_t1 0.38
## reading_t1 0.42
## attitude_total_t1 0.26
## TOTALACIRICHILDT1 0.02
## TOTALACIRIADULTT1 -0.24
## adults_literacy_total_t1
## child_interest_total_t1
## adults_literacy_total_t1
## press4achievement_total_t1 0.03
## availability_t1 0.25
## reading_t1 0.31
## attitude_total_t1 -0.11
## TOTALACIRICHILDT1 -0.32
## TOTALACIRIADULTT1 0.00
## press4achievement_total_t1 availability_t1
## child_interest_total_t1
## adults_literacy_total_t1
## press4achievement_total_t1
## availability_t1 0.43
## reading_t1 0.50* 0.36
## attitude_total_t1 0.23 -0.12
## TOTALACIRICHILDT1 0.26 0.01
## TOTALACIRIADULTT1 0.00 0.26
## reading_t1 attitude_total_t1 TOTALACIRICHILDT1
## child_interest_total_t1
## adults_literacy_total_t1
## press4achievement_total_t1
## availability_t1
## reading_t1
## attitude_total_t1 0.04
## TOTALACIRICHILDT1 -0.03 -0.44
## TOTALACIRIADULTT1 0.08 -0.51* 0.62**