library(readxl)
library(tidyverse)
library(lavaan)
library(semTools)
library(jmRtools) # devtools::install_github("jrosen48/jmRtools")
d <- read_excel("R_Dataset_v2.xlsx")# - expctncy_s__23 (Needs to be reversed)
d$expectancy_success__23 <- sjmisc::rec(d$expectancy_success__23, rec = "1=5;2=4;3=3;4=2;5=1")no missingness in this data
# d %>% select(tam_perceived_usefulness_1:full_cost_emotional_cost_59) %>% complete.cases()
d %>% select(tam_perceived_usefulness_1:full_cost_emotional_cost_59) %>% complete.cases() %>% table()## .
## TRUE
## 249# age
d %>%
skimr::skim(Q3)| Name | Piped data |
| Number of rows | 249 |
| Number of columns | 76 |
| _______________________ | |
| Column type frequency: | |
| numeric | 1 |
| ________________________ | |
| Group variables | None |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| Q3 | 0 | 1 | 24.64 | 7.13 | 18 | 21 | 22 | 26 | 58 | ▇▁▁▁▁ |
# gender
d %>%
janitor::tabyl(Q29)## Q29 n percent valid_percent
## 0 1 0.004016064 0.005434783
## Female 157 0.630522088 0.853260870
## Male 26 0.104417671 0.141304348
## <NA> 65 0.261044177 NA# ethnic background
d %>%
janitor::tabyl(Q31) %>% arrange(desc(n)) %>% data.table::data.table()## Q31 n
## 1: White, Caucasian, European, Not Hispanic 147
## 2: Hispanic or Latino 34
## 3: Asian or Asian American 31
## 4: Black or African American 22
## 5: Hispanic or Latino,White, Caucasian, European, Not Hispanic 5
## 6: Other: 3
## 7: Black or African American,White, Caucasian, European, Not Hispanic 2
## 8: Asian or Asian American,Other: 1
## 9: Asian or Asian American,White, Caucasian, European, Not Hispanic 1
## 10: Black or African American,Hispanic or Latino 1
## 11: Black or African American,Other: 1
## 12: Hispanic or Latino,Other: 1
## percent
## 1: 0.590361446
## 2: 0.136546185
## 3: 0.124497992
## 4: 0.088353414
## 5: 0.020080321
## 6: 0.012048193
## 7: 0.008032129
## 8: 0.004016064
## 9: 0.004016064
## 10: 0.004016064
## 11: 0.004016064
## 12: 0.004016064# english first language
d %>%
janitor::tabyl(Q26)## Q26 n percent
## 0 1 0.004016064
## No 37 0.148594378
## Yes 211 0.847389558# computer access at home, years of usage, hours of use not examinedd %>% select(tam_perceived_usefulness_1:full_cost_emotional_cost_59) %>%
mutate_all(as.numeric) %>%
psych::describe()## vars n mean sd median trimmed mad
## tam_perceived_usefulness_1 1 249 4.35 0.70 4 4.43 1.48
## tam_subjective_norm_2 2 249 3.95 0.78 4 3.98 1.48
## tam_perceived_ease_use_3 3 249 4.15 0.72 4 4.23 0.00
## tam_subjective_norm_4 4 249 3.88 0.80 4 3.89 1.48
## tam_facilitating_condition_5 5 249 4.03 0.77 4 4.10 0.00
## tam_computer_attitudes_6 6 249 4.06 0.86 4 4.14 1.48
## tam_computer_attitudes_7 7 246 4.06 0.85 4 4.14 1.48
## tam_computer_attitudes_8 8 247 4.14 0.84 4 4.25 1.48
## tam_perceived_usefulness_9 9 247 4.16 0.74 4 4.22 1.48
## tam_perceived_ease_use_10 10 249 3.80 0.90 4 3.89 0.00
## tam_perceived_usefulness_11 11 247 3.96 0.84 4 4.02 1.48
## tam_perceived_ease_use_12 12 248 3.14 0.98 3 3.15 1.48
## tam_facilitating_condition_13 13 248 3.59 0.88 4 3.63 1.48
## tam_computer_attitudes_14 14 248 3.61 0.95 4 3.67 1.48
## tam_perceived_usefulness_15 15 248 4.26 0.65 4 4.32 0.00
## tam_perceived_ease_use_16 16 247 3.91 0.81 4 3.99 0.00
## tam_computer_attitudes_17 17 247 3.23 1.05 3 3.19 1.48
## intention_use__18 18 249 4.67 0.79 5 4.66 1.48
## intention_use__19 19 249 4.58 0.72 5 4.57 1.48
## expectancy_success__20 20 249 3.84 0.70 4 3.83 0.00
## expectancy_success__21 21 249 3.83 0.87 4 3.91 0.00
## expectancy_success__22 22 249 3.90 0.74 4 3.92 0.00
## expectancy_success__23 23 249 2.00 0.90 2 1.90 1.48
## expectancy_success__24 24 249 3.39 0.97 3 3.44 1.48
## expectancy_success__25 25 248 3.48 1.01 4 3.54 1.48
## task_value__26 26 249 3.57 0.96 4 3.63 1.48
## task_value_attainment_value_27 27 249 3.61 0.97 4 3.67 1.48
## task_value_utility_value_28 28 249 4.21 0.84 4 4.31 1.48
## task_value_interest_value_29 29 249 3.57 1.06 4 3.63 1.48
## task_value_utility_value_30 30 249 4.31 0.73 4 4.39 1.48
## task_value_attainment_value_31 31 249 3.15 1.17 3 3.19 1.48
## task_value_interest_value_32 32 248 4.00 0.84 4 4.07 1.48
## task_value_attainment_value_33 33 248 3.74 0.95 4 3.82 1.48
## task_value_utility_value_34 34 249 4.24 0.72 4 4.31 1.48
## task_value_utility_value_35 35 249 4.38 0.68 4 4.48 1.48
## task_value_attainment_value_36 36 249 3.14 1.16 3 3.17 1.48
## task_value_interest_value_37 37 248 3.96 0.88 4 4.04 1.48
## task_value_attainment_value_38 38 248 3.63 1.03 4 3.70 1.48
## task_value_utility_value_39 39 249 4.31 0.70 4 4.40 1.48
## task_value_interest_value_40 40 249 3.64 0.98 4 3.69 1.48
## full_cost_emotional_cost_41 41 249 3.59 1.90 3 3.49 1.48
## full_cost_task_effort_cost_42 42 249 3.05 1.70 2 2.90 1.48
## full_cost_loss_valued_alternatives_43 43 249 3.46 1.68 3 3.40 1.48
## full_cost_outside_effort_cost_44 44 248 3.36 1.63 3 3.32 1.48
## full_cost_task_effort_cost_45 45 249 3.12 1.80 2 2.95 1.48
## full_cost_task_effort_cost_46 46 248 2.97 1.73 2 2.79 1.48
## full_cost_outside_effort_cost_47 47 249 3.12 1.73 3 2.97 1.48
## full_cost_emotional_cost_48 48 249 2.99 1.67 2 2.83 1.48
## full_cost_loss_valued_alternatives_49 49 248 3.05 1.65 3 2.92 1.48
## full_cost_outside_effort_cost_50 50 249 3.05 1.65 2 2.93 1.48
## full_cost_task_effort_cost_51 51 249 3.26 1.72 3 3.14 1.48
## full_cost_outside_effort_cost_52 52 249 3.04 1.66 2 2.91 1.48
## full_cost_loss_valued_alternatives_53 53 249 3.08 1.71 2 2.93 1.48
## full_cost_emotional_cost_54 54 249 3.00 1.73 2 2.82 1.48
## full_cost_emotional_cost_55 55 248 2.79 1.78 2 2.58 1.48
## full_cost_loss_valued_alternatives_56 56 249 2.81 1.65 2 2.65 1.48
## full_cost_task_effort_cost_57 57 248 2.90 1.64 2 2.75 1.48
## full_cost_emotional_cost_58 58 249 2.78 1.69 2 2.59 1.48
## full_cost_emotional_cost_59 59 249 3.01 1.87 2 2.77 1.48
## min max range skew kurtosis se
## tam_perceived_usefulness_1 1 5 4 -1.29 3.47 0.04
## tam_subjective_norm_2 1 5 4 -0.37 -0.05 0.05
## tam_perceived_ease_use_3 1 5 4 -1.06 2.58 0.05
## tam_subjective_norm_4 1 5 4 -0.25 -0.28 0.05
## tam_facilitating_condition_5 1 5 4 -0.95 1.67 0.05
## tam_computer_attitudes_6 1 5 4 -0.70 0.05 0.05
## tam_computer_attitudes_7 1 5 4 -0.82 0.63 0.05
## tam_computer_attitudes_8 1 5 4 -0.93 0.71 0.05
## tam_perceived_usefulness_9 1 5 4 -0.62 0.43 0.05
## tam_perceived_ease_use_10 1 5 4 -0.73 0.29 0.06
## tam_perceived_usefulness_11 1 5 4 -0.54 -0.04 0.05
## tam_perceived_ease_use_12 1 5 4 -0.15 -0.88 0.06
## tam_facilitating_condition_13 1 5 4 -0.55 0.15 0.06
## tam_computer_attitudes_14 1 5 4 -0.52 0.10 0.06
## tam_perceived_usefulness_15 1 5 4 -0.93 2.57 0.04
## tam_perceived_ease_use_16 1 5 4 -1.08 1.98 0.05
## tam_computer_attitudes_17 1 5 4 0.09 -0.89 0.07
## intention_use__18 2 6 4 -0.12 -0.20 0.05
## intention_use__19 2 6 4 -0.16 0.13 0.05
## expectancy_success__20 1 5 4 -0.39 0.62 0.04
## expectancy_success__21 1 5 4 -0.99 1.37 0.06
## expectancy_success__22 1 5 4 -0.63 1.20 0.05
## expectancy_success__23 1 5 4 0.90 0.65 0.06
## expectancy_success__24 1 5 4 -0.63 0.32 0.06
## expectancy_success__25 1 5 4 -0.49 0.06 0.06
## task_value__26 1 5 4 -0.36 0.03 0.06
## task_value_attainment_value_27 1 5 4 -0.42 -0.18 0.06
## task_value_utility_value_28 2 5 3 -0.82 -0.06 0.05
## task_value_interest_value_29 1 5 4 -0.35 -0.63 0.07
## task_value_utility_value_30 2 5 3 -0.72 -0.13 0.05
## task_value_attainment_value_31 1 5 4 -0.16 -0.77 0.07
## task_value_interest_value_32 1 5 4 -0.59 0.01 0.05
## task_value_attainment_value_33 1 5 4 -0.54 -0.01 0.06
## task_value_utility_value_34 2 5 3 -0.53 -0.47 0.05
## task_value_utility_value_35 2 5 3 -0.79 0.08 0.04
## task_value_attainment_value_36 1 5 4 -0.11 -0.74 0.07
## task_value_interest_value_37 1 5 4 -0.59 -0.15 0.06
## task_value_attainment_value_38 1 5 4 -0.57 -0.20 0.07
## task_value_utility_value_39 2 5 3 -0.72 0.10 0.04
## task_value_interest_value_40 1 5 4 -0.26 -0.74 0.06
## full_cost_emotional_cost_41 1 9 8 0.55 -0.41 0.12
## full_cost_task_effort_cost_42 1 9 8 0.92 0.52 0.11
## full_cost_loss_valued_alternatives_43 1 9 8 0.34 -0.84 0.11
## full_cost_outside_effort_cost_44 1 7 6 0.20 -1.12 0.10
## full_cost_task_effort_cost_45 1 9 8 0.84 0.27 0.11
## full_cost_task_effort_cost_46 1 9 8 1.02 0.85 0.11
## full_cost_outside_effort_cost_47 1 9 8 0.87 0.56 0.11
## full_cost_emotional_cost_48 1 9 8 0.82 0.15 0.11
## full_cost_loss_valued_alternatives_49 1 9 8 0.90 0.69 0.10
## full_cost_outside_effort_cost_50 1 9 8 0.76 0.05 0.10
## full_cost_task_effort_cost_51 1 9 8 0.71 -0.03 0.11
## full_cost_outside_effort_cost_52 1 9 8 0.88 0.52 0.11
## full_cost_loss_valued_alternatives_53 1 9 8 0.76 -0.05 0.11
## full_cost_emotional_cost_54 1 9 8 0.93 0.40 0.11
## full_cost_emotional_cost_55 1 9 8 1.12 0.83 0.11
## full_cost_loss_valued_alternatives_56 1 9 8 0.93 0.36 0.10
## full_cost_task_effort_cost_57 1 9 8 0.78 -0.21 0.10
## full_cost_emotional_cost_58 1 9 8 1.12 0.98 0.11
## full_cost_emotional_cost_59 1 9 8 1.07 0.67 0.12d %>%
select(tam_perceived_usefulness_1:full_cost_emotional_cost_59) %>%
mutate_all(as.numeric) %>%
corrr::correlate()## # A tibble: 59 x 60
## rowname tam_perceived_u… tam_subjective_… tam_perceived_e… tam_subjective_…
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 tam_pe… NA 0.438 0.478 0.408
## 2 tam_su… 0.438 NA 0.234 0.623
## 3 tam_pe… 0.478 0.234 NA 0.227
## 4 tam_su… 0.408 0.623 0.227 NA
## 5 tam_fa… 0.369 0.404 0.344 0.314
## 6 tam_co… 0.483 0.464 0.366 0.348
## 7 tam_co… 0.475 0.373 0.434 0.219
## 8 tam_co… 0.500 0.320 0.480 0.201
## 9 tam_pe… 0.606 0.481 0.386 0.477
## 10 tam_pe… 0.327 0.359 0.522 0.157
## # … with 49 more rows, and 55 more variables:
## # tam_facilitating_condition_5 <dbl>, tam_computer_attitudes_6 <dbl>,
## # tam_computer_attitudes_7 <dbl>, tam_computer_attitudes_8 <dbl>,
## # tam_perceived_usefulness_9 <dbl>, tam_perceived_ease_use_10 <dbl>,
## # tam_perceived_usefulness_11 <dbl>, tam_perceived_ease_use_12 <dbl>,
## # tam_facilitating_condition_13 <dbl>, tam_computer_attitudes_14 <dbl>,
## # tam_perceived_usefulness_15 <dbl>, tam_perceived_ease_use_16 <dbl>,
## # tam_computer_attitudes_17 <dbl>, intention_use__18 <dbl>,
## # intention_use__19 <dbl>, expectancy_success__20 <dbl>,
## # expectancy_success__21 <dbl>, expectancy_success__22 <dbl>,
## # expectancy_success__23 <dbl>, expectancy_success__24 <dbl>,
## # expectancy_success__25 <dbl>, task_value__26 <dbl>,
## # task_value_attainment_value_27 <dbl>, task_value_utility_value_28 <dbl>,
## # task_value_interest_value_29 <dbl>, task_value_utility_value_30 <dbl>,
## # task_value_attainment_value_31 <dbl>, task_value_interest_value_32 <dbl>,
## # task_value_attainment_value_33 <dbl>, task_value_utility_value_34 <dbl>,
## # task_value_utility_value_35 <dbl>, task_value_attainment_value_36 <dbl>,
## # task_value_interest_value_37 <dbl>, task_value_attainment_value_38 <dbl>,
## # task_value_utility_value_39 <dbl>, task_value_interest_value_40 <dbl>,
## # full_cost_emotional_cost_41 <dbl>, full_cost_task_effort_cost_42 <dbl>,
## # full_cost_loss_valued_alternatives_43 <dbl>,
## # full_cost_outside_effort_cost_44 <dbl>,
## # full_cost_task_effort_cost_45 <dbl>, full_cost_task_effort_cost_46 <dbl>,
## # full_cost_outside_effort_cost_47 <dbl>, full_cost_emotional_cost_48 <dbl>,
## # full_cost_loss_valued_alternatives_49 <dbl>,
## # full_cost_outside_effort_cost_50 <dbl>,
## # full_cost_task_effort_cost_51 <dbl>,
## # full_cost_outside_effort_cost_52 <dbl>,
## # full_cost_loss_valued_alternatives_53 <dbl>,
## # full_cost_emotional_cost_54 <dbl>, full_cost_emotional_cost_55 <dbl>,
## # full_cost_loss_valued_alternatives_56 <dbl>,
## # full_cost_task_effort_cost_57 <dbl>, full_cost_emotional_cost_58 <dbl>,
## # full_cost_emotional_cost_59 <dbl>composite_mean_maker <- function (x, ...) {
out <- dplyr::select(x, ...)
out <- mutate_all(out, as.numeric)
out <- apply(out, 1, function(x) mean(x, na.rm = T))
out[is.nan(out)] <- NA
return(out)
}
o <- d %>%
transmute(perceived_usefulness = composite_mean_maker(., tam_perceived_usefulness_1,
tam_perceived_usefulness_9,
tam_perceived_usefulness_11,
tam_perceived_usefulness_15),
subjective_norms = composite_mean_maker(.,
tam_subjective_norm_2,
tam_subjective_norm_4),
facilitating_conditions = composite_mean_maker(.,
tam_facilitating_condition_5,
tam_facilitating_condition_13),
perceived_ease_use = composite_mean_maker(., tam_perceived_ease_use_3,
tam_perceived_ease_use_10,
# tam_perceived_ease_use_12,
tam_perceived_ease_use_16),
computer_attitudes = composite_mean_maker(., tam_computer_attitudes_6,
tam_computer_attitudes_7,
tam_computer_attitudes_8,
tam_computer_attitudes_14),
#tam_computer_attitudes_17),
attainment = composite_mean_maker(., task_value_attainment_value_27,
task_value_attainment_value_31,
task_value_attainment_value_33,
task_value_attainment_value_36,
task_value_attainment_value_38),
interest = composite_mean_maker(., task_value_interest_value_29,
task_value_interest_value_32,
task_value_interest_value_37,
task_value_interest_value_40),
utility = composite_mean_maker(., task_value_utility_value_28,
task_value_utility_value_30,
task_value_utility_value_34,
task_value_utility_value_35,
task_value_utility_value_39),
expectancy = composite_mean_maker(., expectancy_success__20,
expectancy_success__21,
expectancy_success__22,
#expectancy_success__23,
expectancy_success__24,
expectancy_success__25),
task_value = composite_mean_maker(., task_value_attainment_value_27,
task_value_attainment_value_31,
task_value_attainment_value_33,
task_value_attainment_value_36,
task_value_attainment_value_38,
task_value_interest_value_29,
task_value_interest_value_32,
task_value_interest_value_37,
task_value_interest_value_40,
task_value_utility_value_28,
task_value_utility_value_30,
task_value_utility_value_34,
task_value_utility_value_35,
task_value_utility_value_39),
task_effort = composite_mean_maker(., full_cost_task_effort_cost_42,
full_cost_task_effort_cost_45,
full_cost_task_effort_cost_46,
full_cost_task_effort_cost_51,
full_cost_task_effort_cost_57),
outside_effort = composite_mean_maker(., full_cost_outside_effort_cost_44,
full_cost_outside_effort_cost_47,
full_cost_outside_effort_cost_50,
full_cost_outside_effort_cost_52),
lova = composite_mean_maker(., full_cost_loss_valued_alternatives_43,
full_cost_loss_valued_alternatives_49,
full_cost_loss_valued_alternatives_53,
full_cost_loss_valued_alternatives_56),
emotional_costs = composite_mean_maker(., full_cost_emotional_cost_41,
full_cost_emotional_cost_48,
full_cost_emotional_cost_54,
full_cost_emotional_cost_55,
full_cost_emotional_cost_58,
full_cost_emotional_cost_59),
cost = composite_mean_maker(., full_cost_task_effort_cost_42,
full_cost_task_effort_cost_45,
full_cost_task_effort_cost_46,
full_cost_task_effort_cost_51,
full_cost_task_effort_cost_57,
full_cost_outside_effort_cost_44,
full_cost_outside_effort_cost_47,
full_cost_outside_effort_cost_50,
full_cost_outside_effort_cost_52,
full_cost_loss_valued_alternatives_43,
full_cost_loss_valued_alternatives_49,
full_cost_loss_valued_alternatives_53,
full_cost_loss_valued_alternatives_56,
full_cost_emotional_cost_41,
full_cost_emotional_cost_48,
full_cost_emotional_cost_54,
full_cost_emotional_cost_55,
full_cost_emotional_cost_58,
full_cost_emotional_cost_59),
behavioral_intentions = composite_mean_maker(., intention_use__18, intention_use__19),
Site)o %>%
select(perceived_usefulness,
perceived_ease_use,
computer_attitudes,
behavioral_intentions,
subjective_norms,
facilitating_conditions,
attainment,
interest,
utility,
expectancy,
task_effort,
outside_effort,
lova,
emotional_costs) %>%
psych::describe()## vars n mean sd median trimmed mad min max range
## perceived_usefulness 1 249 4.18 0.58 4.00 4.21 0.74 1.0 5.00 4.00
## perceived_ease_use 2 249 3.96 0.69 4.00 4.01 0.49 1.0 5.00 4.00
## computer_attitudes 3 249 3.97 0.75 4.00 4.02 0.74 1.0 5.00 4.00
## behavioral_intentions 4 249 4.62 0.67 5.00 4.64 0.00 2.0 6.00 4.00
## subjective_norms 5 249 3.92 0.71 4.00 3.93 0.74 1.0 5.00 4.00
## facilitating_conditions 6 249 3.81 0.74 4.00 3.84 0.74 1.0 5.00 4.00
## attainment 7 249 3.46 0.87 3.40 3.48 0.89 1.2 5.00 3.80
## interest 8 249 3.79 0.83 4.00 3.84 0.74 1.0 5.00 4.00
## utility 9 249 4.29 0.60 4.40 4.35 0.59 2.0 5.00 3.00
## expectancy 10 249 3.68 0.67 3.60 3.70 0.59 1.2 5.00 3.80
## task_effort 11 249 3.06 1.56 2.60 2.94 1.48 1.0 9.00 8.00
## outside_effort 12 249 3.15 1.51 2.75 3.07 1.48 1.0 8.25 7.25
## lova 13 249 3.10 1.47 2.75 3.02 1.48 1.0 9.00 8.00
## emotional_costs 14 249 3.03 1.57 2.50 2.90 1.48 1.0 9.00 8.00
## skew kurtosis se
## perceived_usefulness -0.91 3.08 0.04
## perceived_ease_use -1.02 2.02 0.04
## computer_attitudes -0.75 0.63 0.05
## behavioral_intentions -0.43 0.64 0.04
## subjective_norms -0.41 0.42 0.05
## facilitating_conditions -0.76 1.40 0.05
## attainment -0.27 -0.32 0.05
## interest -0.52 -0.20 0.05
## utility -0.71 0.29 0.04
## expectancy -0.39 0.75 0.04
## task_effort 0.88 0.60 0.10
## outside_effort 0.53 -0.49 0.10
## lova 0.68 0.17 0.09
## emotional_costs 0.89 0.53 0.10o %>%
select(perceived_usefulness,
perceived_ease_use,
computer_attitudes,
behavioral_intentions,
subjective_norms,
facilitating_conditions,
attainment,
interest,
utility,
expectancy,
task_effort,
outside_effort,
lova,
emotional_costs) %>%
apaTables::apa.cor.table(filename = "composite-descriptives.doc")##
##
## Means, standard deviations, and correlations with confidence intervals
##
##
## Variable M SD 1 2 3
## 1. perceived_usefulness 4.18 0.58
##
## 2. perceived_ease_use 3.96 0.69 .49**
## [.39, .58]
##
## 3. computer_attitudes 3.97 0.75 .62** .67**
## [.53, .69] [.59, .73]
##
## 4. behavioral_intentions 4.62 0.67 .20** .20** .21**
## [.08, .32] [.08, .32] [.08, .32]
##
## 5. subjective_norms 3.92 0.71 .56** .29** .39**
## [.47, .64] [.17, .40] [.28, .49]
##
## 6. facilitating_conditions 3.81 0.74 .45** .51** .49**
## [.34, .54] [.41, .60] [.39, .58]
##
## 7. attainment 3.46 0.87 .42** .44** .62**
## [.31, .52] [.34, .54] [.53, .69]
##
## 8. interest 3.79 0.83 .46** .53** .76**
## [.36, .55] [.43, .61] [.70, .81]
##
## 9. utility 4.29 0.60 .48** .37** .49**
## [.38, .57] [.26, .47] [.39, .58]
##
## 10. expectancy 3.68 0.67 .46** .31** .38**
## [.36, .56] [.19, .42] [.26, .48]
##
## 11. task_effort 3.06 1.56 -.28** -.42** -.41**
## [-.39, -.16] [-.51, -.31] [-.51, -.30]
##
## 12. outside_effort 3.15 1.51 -.31** -.40** -.40**
## [-.42, -.19] [-.50, -.29] [-.50, -.29]
##
## 13. lova 3.10 1.47 -.34** -.42** -.47**
## [-.44, -.22] [-.51, -.31] [-.56, -.36]
##
## 14. emotional_costs 3.03 1.57 -.30** -.51** -.46**
## [-.41, -.18] [-.60, -.41] [-.55, -.36]
##
## 4 5 6 7 8 9
##
##
##
##
##
##
##
##
##
##
##
## .12
## [-.00, .24]
##
## .19** .37**
## [.07, .31] [.25, .47]
##
## .12 .39** .36**
## [-.01, .24] [.28, .49] [.25, .47]
##
## .16* .40** .45** .76**
## [.03, .27] [.29, .50] [.34, .54] [.70, .81]
##
## .22** .41** .33** .64** .67**
## [.10, .34] [.30, .50] [.22, .44] [.56, .71] [.59, .73]
##
## .12 .41** .35** .49** .47** .51**
## [-.00, .24] [.30, .51] [.23, .45] [.39, .58] [.37, .56] [.41, .60]
##
## -.14* -.18** -.29** -.30** -.36** -.34**
## [-.26, -.02] [-.30, -.06] [-.40, -.17] [-.41, -.19] [-.46, -.25] [-.44, -.22]
##
## -.17** -.18** -.29** -.32** -.36** -.35**
## [-.29, -.04] [-.30, -.06] [-.40, -.17] [-.42, -.20] [-.47, -.25] [-.45, -.23]
##
## -.15* -.18** -.31** -.35** -.41** -.35**
## [-.27, -.03] [-.30, -.06] [-.41, -.19] [-.46, -.24] [-.51, -.30] [-.45, -.23]
##
## -.16* -.15* -.34** -.33** -.39** -.30**
## [-.28, -.04] [-.27, -.03] [-.44, -.22] [-.44, -.22] [-.49, -.28] [-.41, -.19]
##
## 10 11 12 13
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
##
## -.30**
## [-.41, -.18]
##
## -.32** .93**
## [-.43, -.20] [.92, .95]
##
## -.35** .88** .90**
## [-.46, -.24] [.85, .91] [.87, .92]
##
## -.32** .90** .88** .88**
## [-.43, -.21] [.87, .92] [.84, .90] [.85, .91]
##
##
## Note. M and SD are used to represent mean and standard deviation, respectively.
## Values in square brackets indicate the 95% confidence interval.
## The confidence interval is a plausible range of population correlations
## that could have caused the sample correlation (Cumming, 2014).
## * indicates p < .05. ** indicates p < .01.
## o %>%
group_by(Site) %>%
skimr::skim() %>%
DT::datatable()res.man <- manova(cbind(perceived_usefulness,
perceived_ease_use,
computer_attitudes,
behavioral_intentions,
subjective_norms,
facilitating_conditions,
attainment,
interest,
utility,
expectancy,
task_effort,
outside_effort,
lova,
emotional_costs) ~ Site, data = o)
summary(res.man)## Df Pillai approx F num Df den Df Pr(>F)
## Site 2 0.14741 1.33 28 468 0.123
## Residuals 246# summary.aov(res.man)man_tam <- manova(cbind(perceived_usefulness,
perceived_ease_use,
computer_attitudes,
behavioral_intentions,
subjective_norms,
facilitating_conditions) ~ Site, data = o)
man_evt <- manova(cbind(attainment,
interest,
utility,
expectancy) ~ Site, data = o)
man_cost <- manova(cbind(task_effort,
outside_effort,
lova,
emotional_costs) ~ Site, data = o)
summary(man_tam)## Df Pillai approx F num Df den Df Pr(>F)
## Site 2 0.082617 1.7379 12 484 0.05611 .
## Residuals 246
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1#summary.aov(man_tam)
summary(man_evt)## Df Pillai approx F num Df den Df Pr(>F)
## Site 2 0.022545 0.69546 8 488 0.6957
## Residuals 246#summary.aov(man_evt)
summary(man_cost)## Df Pillai approx F num Df den Df Pr(>F)
## Site 2 0.033796 1.0485 8 488 0.3984
## Residuals 246#summary.aov(man_cost)Changes made: - tm_prcvd_s__12 - tam_perceived_ease_use_12 - done - tm_cmptr_tt_17 - tam_computer_attitudes_17 - done
fitmod <- '
# factors
subjective_norms =~
tam_subjective_norm_2 +
tam_subjective_norm_4
facilitating_conditions =~
tam_facilitating_condition_5 +
tam_facilitating_condition_13
'
m1 <- cfa(fitmod, data = d)
summary(m1, fit.measures = TRUE, standardized = TRUE, rsquare = TRUE)## lavaan 0.6-5 ended normally after 27 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 9
##
## Number of observations 249
##
## Model Test User Model:
##
## Test statistic 3.822
## Degrees of freedom 1
## P-value (Chi-square) 0.051
##
## Model Test Baseline Model:
##
## Test statistic 285.066
## Degrees of freedom 6
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.990
## Tucker-Lewis Index (TLI) 0.939
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -1056.151
## Loglikelihood unrestricted model (H1) NA
##
## Akaike (AIC) 2130.303
## Bayesian (BIC) 2161.960
## Sample-size adjusted Bayesian (BIC) 2133.429
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.106
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.228
## P-value RMSEA <= 0.05 0.125
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.019
##
## Parameter Estimates:
##
## Information Expected
## Information saturated (h1) model Structured
## Standard errors Standard
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv
## subjective_norms =~
## tm_sbjctv_nr_2 1.000 0.719
## tm_sbjctv_nr_4 0.751 0.124 6.062 0.000 0.540
## facilitating_conditions =~
## tm_fclttng_c_5 1.000 0.692
## tm_fclttng__13 0.844 0.142 5.923 0.000 0.584
## Std.all
##
## 0.921
## 0.677
##
## 0.899
## 0.667
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## subjective_norms ~~
## fclttng_cndtns 0.244 0.041 5.947 0.000 0.491 0.491
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .tm_sbjctv_nr_2 0.092 0.078 1.175 0.240 0.092 0.151
## .tm_sbjctv_nr_4 0.345 0.054 6.438 0.000 0.345 0.542
## .tm_fclttng_c_5 0.114 0.075 1.530 0.126 0.114 0.192
## .tm_fclttng__13 0.425 0.065 6.545 0.000 0.425 0.555
## subjectiv_nrms 0.516 0.094 5.466 0.000 1.000 1.000
## fclttng_cndtns 0.479 0.090 5.300 0.000 1.000 1.000
##
## R-Square:
## Estimate
## tm_sbjctv_nr_2 0.849
## tm_sbjctv_nr_4 0.458
## tm_fclttng_c_5 0.808
## tm_fclttng__13 0.445reliability(m1)## subjective_norms facilitating_conditions total
## alpha 0.7679555 0.7460645 0.7259727
## omega 0.7838175 0.7514774 0.8308124
## omega2 0.7838175 0.7514774 0.8308124
## omega3 0.7838175 0.7514774 0.8380743
## avevar 0.6490670 0.6036118 0.6253376# run the code below to confirm that the above gives the same values for alpha
# psych::alpha(data.frame(d$tam_subjective_norm_2, d$tam_subjective_norm_4))
lavInspect(m1)## $lambda
## sbjct_ fcltt_
## tam_subjective_norm_2 0 0
## tam_subjective_norm_4 1 0
## tam_facilitating_condition_5 0 0
## tam_facilitating_condition_13 0 2
##
## $theta
## tm___2 tm___4 tm___5 t___13
## tam_subjective_norm_2 3
## tam_subjective_norm_4 0 4
## tam_facilitating_condition_5 0 0 5
## tam_facilitating_condition_13 0 0 0 6
##
## $psi
## sbjct_ fcltt_
## subjective_norms 7
## facilitating_conditions 9 8fitmod <- '
# factors
perceived_usefulness =~
tam_perceived_usefulness_1 +
tam_perceived_usefulness_9 +
tam_perceived_usefulness_11 +
tam_perceived_usefulness_15
perceived_ease_use =~
tam_perceived_ease_use_3 +
tam_perceived_ease_use_10 +
# tam_perceived_ease_use_12 +
tam_perceived_ease_use_16
'
m2 <- cfa(fitmod, data = d)
summary(m2, fit.measures = TRUE, standardized = TRUE, rsquare = TRUE)## lavaan 0.6-5 ended normally after 26 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 15
##
## Number of observations 249
##
## Model Test User Model:
##
## Test statistic 73.021
## Degrees of freedom 13
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 705.039
## Degrees of freedom 21
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.912
## Tucker-Lewis Index (TLI) 0.858
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -1681.858
## Loglikelihood unrestricted model (H1) NA
##
## Akaike (AIC) 3393.716
## Bayesian (BIC) 3446.477
## Sample-size adjusted Bayesian (BIC) 3398.927
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.136
## 90 Percent confidence interval - lower 0.107
## 90 Percent confidence interval - upper 0.167
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.063
##
## Parameter Estimates:
##
## Information Expected
## Information saturated (h1) model Structured
## Standard errors Standard
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## perceived_usefulness =~
## tm_prcvd_sfl_1 1.000 0.553 0.796
## tm_prcvd_sfl_9 1.020 0.090 11.337 0.000 0.565 0.762
## tm_prcvd_sf_11 0.863 0.102 8.485 0.000 0.478 0.570
## tm_prcvd_sf_15 0.861 0.079 10.915 0.000 0.477 0.729
## perceived_ease_use =~
## tm_prcvd_s_s_3 1.000 0.469 0.648
## tm_prcvd_s__10 1.580 0.162 9.725 0.000 0.740 0.823
## tm_prcvd_s__16 1.387 0.143 9.679 0.000 0.650 0.804
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## perceived_usefulness ~~
## perceived_es_s 0.154 0.026 5.849 0.000 0.593 0.593
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .tm_prcvd_sfl_1 0.177 0.025 7.199 0.000 0.177 0.366
## .tm_prcvd_sfl_9 0.230 0.029 7.973 0.000 0.230 0.419
## .tm_prcvd_sf_11 0.475 0.047 10.094 0.000 0.475 0.675
## .tm_prcvd_sf_15 0.200 0.023 8.574 0.000 0.200 0.468
## .tm_prcvd_s_s_3 0.303 0.032 9.485 0.000 0.303 0.580
## .tm_prcvd_s__10 0.260 0.044 5.946 0.000 0.260 0.322
## .tm_prcvd_s__16 0.230 0.035 6.514 0.000 0.230 0.353
## percevd_sflnss 0.306 0.044 6.890 0.000 1.000 1.000
## perceived_es_s 0.220 0.042 5.264 0.000 1.000 1.000
##
## R-Square:
## Estimate
## tm_prcvd_sfl_1 0.634
## tm_prcvd_sfl_9 0.581
## tm_prcvd_sf_11 0.325
## tm_prcvd_sf_15 0.532
## tm_prcvd_s_s_3 0.420
## tm_prcvd_s__10 0.678
## tm_prcvd_s__16 0.647reliability(m2)## perceived_usefulness perceived_ease_use total
## alpha 0.7993080 0.7953703 0.8285637
## omega 0.7988605 0.8131696 0.8678772
## omega2 0.7988605 0.8131696 0.8678772
## omega3 0.7956951 0.8181357 0.8610541
## avevar 0.4997926 0.5998507 0.5476780fitmod <- '
# factors
computer_attitudes =~
tam_computer_attitudes_6 +
tam_computer_attitudes_7 +
tam_computer_attitudes_8 +
tam_computer_attitudes_14
# tam_computer_attitudes_17
'
m3 <- cfa(fitmod, data = d)
summary(m3, fit.measures = TRUE, standardized = TRUE, rsquare = TRUE)## lavaan 0.6-5 ended normally after 20 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 8
##
## Number of observations 249
##
## Model Test User Model:
##
## Test statistic 8.878
## Degrees of freedom 2
## P-value (Chi-square) 0.012
##
## Model Test Baseline Model:
##
## Test statistic 563.138
## Degrees of freedom 6
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.988
## Tucker-Lewis Index (TLI) 0.963
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -1000.114
## Loglikelihood unrestricted model (H1) NA
##
## Akaike (AIC) 2016.228
## Bayesian (BIC) 2044.367
## Sample-size adjusted Bayesian (BIC) 2019.007
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.118
## 90 Percent confidence interval - lower 0.047
## 90 Percent confidence interval - upper 0.201
## P-value RMSEA <= 0.05 0.056
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.021
##
## Parameter Estimates:
##
## Information Expected
## Information saturated (h1) model Structured
## Standard errors Standard
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## computer_attitudes =~
## tm_cmptr_ttt_6 1.000 0.673 0.780
## tm_cmptr_ttt_7 1.150 0.076 15.113 0.000 0.774 0.911
## tm_cmptr_ttt_8 1.020 0.074 13.784 0.000 0.686 0.822
## tm_cmptr_tt_14 1.026 0.086 11.930 0.000 0.690 0.728
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .tm_cmptr_ttt_6 0.292 0.032 9.184 0.000 0.292 0.392
## .tm_cmptr_ttt_7 0.122 0.024 5.129 0.000 0.122 0.169
## .tm_cmptr_ttt_8 0.226 0.027 8.398 0.000 0.226 0.325
## .tm_cmptr_tt_14 0.422 0.043 9.765 0.000 0.422 0.470
## computer_tttds 0.452 0.064 7.076 0.000 1.000 1.000
##
## R-Square:
## Estimate
## tm_cmptr_ttt_6 0.608
## tm_cmptr_ttt_7 0.831
## tm_cmptr_ttt_8 0.675
## tm_cmptr_tt_14 0.530reliability(m3)## computer_attitudes total
## alpha 0.8825973 0.8825973
## omega 0.8823508 0.8823508
## omega2 0.8823508 0.8823508
## omega3 0.8800392 0.8800392
## avevar 0.6528908 0.6528908fitmod <- '
attainment =~
task_value_attainment_value_27 +
task_value_attainment_value_31 +
task_value_attainment_value_33 +
task_value_attainment_value_36 +
task_value_attainment_value_38
interest =~
task_value_interest_value_29 +
task_value_interest_value_32 +
task_value_interest_value_37 +
task_value_interest_value_40
utility =~
task_value_utility_value_28 +
task_value_utility_value_30 +
task_value_utility_value_34 +
task_value_utility_value_35 +
task_value_utility_value_39
expectancy =~
expectancy_success__20 +
expectancy_success__21 +
expectancy_success__22 +
# expectancy_success__23 +
expectancy_success__24 +
expectancy_success__25
'
m4 <- cfa(fitmod, data = d)
summary(m4, fit.measures = TRUE, standardized = TRUE, rsquare = TRUE)## lavaan 0.6-5 ended normally after 58 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 44
##
## Number of observations 249
##
## Model Test User Model:
##
## Test statistic 524.812
## Degrees of freedom 146
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 3249.972
## Degrees of freedom 171
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.877
## Tucker-Lewis Index (TLI) 0.856
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -4744.785
## Loglikelihood unrestricted model (H1) NA
##
## Akaike (AIC) 9577.569
## Bayesian (BIC) 9732.337
## Sample-size adjusted Bayesian (BIC) 9592.855
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.102
## 90 Percent confidence interval - lower 0.093
## 90 Percent confidence interval - upper 0.112
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.076
##
## Parameter Estimates:
##
## Information Expected
## Information saturated (h1) model Structured
## Standard errors Standard
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## attainment =~
## tsk_vl_ttn__27 1.000 0.773 0.800
## tsk_vl_ttn__31 1.240 0.087 14.297 0.000 0.959 0.821
## tsk_vl_ttn__33 0.759 0.075 10.083 0.000 0.587 0.618
## tsk_vl_ttn__36 1.235 0.086 14.339 0.000 0.955 0.822
## tsk_vl_ttn__38 1.025 0.077 13.283 0.000 0.793 0.775
## interest =~
## tsk_vl_ntr__29 1.000 0.836 0.787
## tsk_vl_ntr__32 0.835 0.057 14.554 0.000 0.698 0.836
## tsk_vl_ntr__37 0.894 0.060 14.895 0.000 0.748 0.851
## tsk_vl_ntr__40 1.024 0.066 15.407 0.000 0.856 0.874
## utility =~
## tsk_vl_tlt__28 1.000 0.567 0.680
## tsk_vl_tlt__30 0.966 0.090 10.750 0.000 0.548 0.756
## tsk_vl_tlt__34 1.108 0.091 12.158 0.000 0.629 0.877
## tsk_vl_tlt__35 1.009 0.086 11.799 0.000 0.572 0.843
## tsk_vl_tlt__39 0.845 0.086 9.856 0.000 0.480 0.686
## expectancy =~
## expctncy_s__20 1.000 0.478 0.683
## expctncy_s__21 1.166 0.132 8.850 0.000 0.558 0.639
## expctncy_s__22 0.962 0.111 8.687 0.000 0.460 0.626
## expctncy_s__24 1.554 0.150 10.329 0.000 0.744 0.768
## expctncy_s__25 1.673 0.158 10.583 0.000 0.801 0.795
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## attainment ~~
## interest 0.535 0.067 8.001 0.000 0.828 0.828
## utility 0.293 0.044 6.731 0.000 0.668 0.668
## expectancy 0.210 0.035 6.036 0.000 0.568 0.568
## interest ~~
## utility 0.333 0.048 6.895 0.000 0.703 0.703
## expectancy 0.221 0.037 5.933 0.000 0.551 0.551
## utility ~~
## expectancy 0.153 0.027 5.749 0.000 0.564 0.564
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .tsk_vl_ttn__27 0.337 0.037 9.144 0.000 0.337 0.361
## .tsk_vl_ttn__31 0.446 0.051 8.812 0.000 0.446 0.327
## .tsk_vl_ttn__33 0.557 0.053 10.464 0.000 0.557 0.618
## .tsk_vl_ttn__36 0.437 0.050 8.778 0.000 0.437 0.324
## .tsk_vl_ttn__38 0.418 0.044 9.457 0.000 0.418 0.400
## .tsk_vl_ntr__29 0.429 0.045 9.597 0.000 0.429 0.380
## .tsk_vl_ntr__32 0.210 0.024 8.923 0.000 0.210 0.302
## .tsk_vl_ntr__37 0.213 0.025 8.617 0.000 0.213 0.276
## .tsk_vl_ntr__40 0.227 0.028 8.024 0.000 0.227 0.236
## .tsk_vl_tlt__28 0.374 0.037 10.176 0.000 0.374 0.537
## .tsk_vl_tlt__30 0.225 0.023 9.622 0.000 0.225 0.428
## .tsk_vl_tlt__34 0.119 0.016 7.295 0.000 0.119 0.232
## .tsk_vl_tlt__35 0.133 0.016 8.274 0.000 0.133 0.289
## .tsk_vl_tlt__39 0.258 0.025 10.143 0.000 0.258 0.529
## .expctncy_s__20 0.262 0.028 9.482 0.000 0.262 0.534
## .expctncy_s__21 0.450 0.046 9.838 0.000 0.450 0.591
## .expctncy_s__22 0.328 0.033 9.928 0.000 0.328 0.608
## .expctncy_s__24 0.384 0.046 8.361 0.000 0.384 0.410
## .expctncy_s__25 0.374 0.048 7.842 0.000 0.374 0.369
## attainment 0.598 0.081 7.384 0.000 1.000 1.000
## interest 0.699 0.096 7.265 0.000 1.000 1.000
## utility 0.322 0.055 5.885 0.000 1.000 1.000
## expectancy 0.229 0.040 5.729 0.000 1.000 1.000
##
## R-Square:
## Estimate
## tsk_vl_ttn__27 0.639
## tsk_vl_ttn__31 0.673
## tsk_vl_ttn__33 0.382
## tsk_vl_ttn__36 0.676
## tsk_vl_ttn__38 0.600
## tsk_vl_ntr__29 0.620
## tsk_vl_ntr__32 0.698
## tsk_vl_ntr__37 0.724
## tsk_vl_ntr__40 0.764
## tsk_vl_tlt__28 0.463
## tsk_vl_tlt__30 0.572
## tsk_vl_tlt__34 0.768
## tsk_vl_tlt__35 0.711
## tsk_vl_tlt__39 0.471
## expctncy_s__20 0.466
## expctncy_s__21 0.409
## expctncy_s__22 0.392
## expctncy_s__24 0.590
## expctncy_s__25 0.631reliability(m4)## attainment interest utility expectancy total
## alpha 0.8738405 0.8982114 0.8733059 0.8282388 0.9339553
## omega 0.8828526 0.9012426 0.8756847 0.8371888 0.9533286
## omega2 0.8828526 0.9012426 0.8756847 0.8371888 0.9533286
## omega3 0.8892302 0.9033106 0.8774662 0.8332584 0.9334171
## avevar 0.6079011 0.6966856 0.5866401 0.5197320 0.6033295fitmod <- '
task_effort =~
full_cost_task_effort_cost_42 +
full_cost_task_effort_cost_45 +
full_cost_task_effort_cost_46 +
full_cost_task_effort_cost_51 +
full_cost_task_effort_cost_57
outside_effort =~
full_cost_outside_effort_cost_44 +
full_cost_outside_effort_cost_47 +
full_cost_outside_effort_cost_50 +
full_cost_outside_effort_cost_52
lova =~
full_cost_loss_valued_alternatives_43 +
full_cost_loss_valued_alternatives_49 +
full_cost_loss_valued_alternatives_53 +
full_cost_loss_valued_alternatives_56
emotional_costs =~
full_cost_emotional_cost_41 +
full_cost_emotional_cost_48 +
full_cost_emotional_cost_54 +
full_cost_emotional_cost_55 +
full_cost_emotional_cost_58 +
full_cost_emotional_cost_59
'
m6 <- cfa(fitmod, data = d)
summary(m6, fit.measures = TRUE, standardized = TRUE, rsquare = TRUE)## lavaan 0.6-5 ended normally after 77 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 44
##
## Number of observations 249
##
## Model Test User Model:
##
## Test statistic 911.894
## Degrees of freedom 146
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 6489.349
## Degrees of freedom 171
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.879
## Tucker-Lewis Index (TLI) 0.858
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -6459.973
## Loglikelihood unrestricted model (H1) NA
##
## Akaike (AIC) 13007.946
## Bayesian (BIC) 13162.714
## Sample-size adjusted Bayesian (BIC) 13023.232
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.145
## 90 Percent confidence interval - lower 0.136
## 90 Percent confidence interval - upper 0.154
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.041
##
## Parameter Estimates:
##
## Information Expected
## Information saturated (h1) model Structured
## Standard errors Standard
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## task_effort =~
## fll_cst_t___42 1.000 1.576 0.931
## fll_cst_t___45 1.010 0.042 23.902 0.000 1.591 0.887
## fll_cst_t___46 1.003 0.038 26.439 0.000 1.580 0.916
## fll_cst_t___51 0.884 0.046 19.090 0.000 1.392 0.813
## fll_cst_t___57 0.938 0.037 25.277 0.000 1.478 0.904
## outside_effort =~
## fll_cst_t___44 1.000 1.266 0.779
## fll_cst_t___47 1.158 0.076 15.332 0.000 1.465 0.848
## fll_cst_t___50 1.185 0.070 16.923 0.000 1.500 0.912
## fll_cst_t___52 1.203 0.071 17.056 0.000 1.522 0.917
## lova =~
## fll_cst_l___43 1.000 1.185 0.708
## fll_cst_l___49 1.191 0.090 13.267 0.000 1.411 0.857
## fll_cst_l___53 1.230 0.093 13.189 0.000 1.458 0.852
## fll_cst_l___56 1.282 0.090 14.296 0.000 1.519 0.924
## emotional_costs =~
## fll_cst_mt__41 1.000 1.304 0.689
## fll_cst_mt__48 1.126 0.086 13.114 0.000 1.468 0.880
## fll_cst_mt__54 1.172 0.089 13.211 0.000 1.528 0.887
## fll_cst_mt__55 1.215 0.091 13.294 0.000 1.585 0.893
## fll_cst_mt__58 1.197 0.087 13.720 0.000 1.560 0.925
## fll_cst_mt__59 1.254 0.096 13.088 0.000 1.636 0.878
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## task_effort ~~
## outside_effort 1.994 0.212 9.395 0.000 1.000 1.000
## lova 1.766 0.204 8.650 0.000 0.946 0.946
## emotional_csts 1.952 0.229 8.531 0.000 0.950 0.950
## outside_effort ~~
## lova 1.457 0.179 8.128 0.000 0.971 0.971
## emotional_csts 1.545 0.195 7.923 0.000 0.936 0.936
## lova ~~
## emotional_csts 1.488 0.195 7.637 0.000 0.963 0.963
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .fll_cst_t___42 0.382 0.041 9.406 0.000 0.382 0.133
## .fll_cst_t___45 0.683 0.067 10.201 0.000 0.683 0.213
## .fll_cst_t___46 0.479 0.049 9.781 0.000 0.479 0.161
## .fll_cst_t___51 0.993 0.093 10.666 0.000 0.993 0.339
## .fll_cst_t___57 0.491 0.049 9.996 0.000 0.491 0.184
## .fll_cst_t___44 1.040 0.096 10.801 0.000 1.040 0.394
## .fll_cst_t___47 0.837 0.080 10.515 0.000 0.837 0.280
## .fll_cst_t___50 0.457 0.047 9.709 0.000 0.457 0.169
## .fll_cst_t___52 0.440 0.046 9.574 0.000 0.440 0.160
## .fll_cst_l___43 1.399 0.130 10.739 0.000 1.399 0.499
## .fll_cst_l___49 0.721 0.073 9.938 0.000 0.721 0.266
## .fll_cst_l___53 0.804 0.080 9.995 0.000 0.804 0.275
## .fll_cst_l___56 0.396 0.048 8.279 0.000 0.396 0.146
## .fll_cst_mt__41 1.883 0.174 10.837 0.000 1.883 0.526
## .fll_cst_mt__48 0.627 0.063 9.919 0.000 0.627 0.225
## .fll_cst_mt__54 0.632 0.064 9.822 0.000 0.632 0.213
## .fll_cst_mt__55 0.636 0.065 9.729 0.000 0.636 0.202
## .fll_cst_mt__58 0.412 0.046 8.999 0.000 0.412 0.145
## .fll_cst_mt__59 0.794 0.080 9.942 0.000 0.794 0.229
## task_effort 2.483 0.255 9.720 0.000 1.000 1.000
## outside_effort 1.602 0.219 7.315 0.000 1.000 1.000
## lova 1.404 0.221 6.365 0.000 1.000 1.000
## emotional_csts 1.700 0.276 6.152 0.000 1.000 1.000
##
## R-Square:
## Estimate
## fll_cst_t___42 0.867
## fll_cst_t___45 0.787
## fll_cst_t___46 0.839
## fll_cst_t___51 0.661
## fll_cst_t___57 0.816
## fll_cst_t___44 0.606
## fll_cst_t___47 0.720
## fll_cst_t___50 0.831
## fll_cst_t___52 0.840
## fll_cst_l___43 0.501
## fll_cst_l___49 0.734
## fll_cst_l___53 0.725
## fll_cst_l___56 0.854
## fll_cst_mt__41 0.474
## fll_cst_mt__48 0.775
## fll_cst_mt__54 0.787
## fll_cst_mt__55 0.798
## fll_cst_mt__58 0.855
## fll_cst_mt__59 0.771reliability(m6)## task_effort outside_effort lova emotional_costs total
## alpha 0.9486422 0.9240200 0.9026252 0.9438111 0.9800623
## omega 0.9503830 0.9226744 0.9033944 0.9430058 0.9818120
## omega2 0.9503830 0.9226744 0.9033944 0.9430058 0.9818120
## omega3 0.9539666 0.9162184 0.8998393 0.9366268 0.9778926
## avevar 0.7934170 0.7498741 0.7021160 0.7348412 0.7467073fitmod <- '
behavioral_intentions =~
intention_use__18 +
intention_use__19
'
m8 <- cfa(fitmod, data = d)
summary(m8, fit.measures = TRUE, standardized = TRUE, rsquare = TRUE)## lavaan 0.6-5 ended normally after 16 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 4
##
## Number of observations 249
##
## Model Test User Model:
##
## Test statistic NA
## Degrees of freedom -1
## P-value (Unknown) NA
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) NA
## Tucker-Lewis Index (TLI) NA
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -515.491
## Loglikelihood unrestricted model (H1) -515.491
##
## Akaike (AIC) 1038.981
## Bayesian (BIC) 1053.051
## Sample-size adjusted Bayesian (BIC) 1040.371
##
## Root Mean Square Error of Approximation:
##
## RMSEA NA
## 90 Percent confidence interval - lower NA
## 90 Percent confidence interval - upper NA
## P-value RMSEA <= 0.05 NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.000
##
## Parameter Estimates:
##
## Information Expected
## Information saturated (h1) model Structured
## Standard errors Standard
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv
## behavioral_intentions =~
## intentin_s__18 1.000 0.740
## intentin_s__19 0.596 NA 0.441
## Std.all
##
## 0.937
## 0.614
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .intentin_s__18 0.076 NA 0.076 0.122
## .intentin_s__19 0.322 NA 0.322 0.623
## behavrl_ntntns 0.548 NA 1.000 1.000
##
## R-Square:
## Estimate
## intentin_s__18 0.878
## intentin_s__19 0.377reliability(m8)## behavioral_intentions total
## alpha 0.7285285 0.7285285
## omega 0.7783599 0.7783599
## omega2 0.7783599 0.7783599
## omega3 0.7783599 0.7783599
## avevar 0.6513644 0.6513644fitmod <- '
# factors
subjective_norms =~
tam_subjective_norm_2 +
tam_subjective_norm_4
facilitating_conditions =~
tam_facilitating_condition_5 +
tam_facilitating_condition_13
perceived_usefulness =~
tam_perceived_usefulness_1 +
tam_perceived_usefulness_9 +
tam_perceived_usefulness_11 +
tam_perceived_usefulness_15
perceived_ease_use =~
tam_perceived_ease_use_3 +
tam_perceived_ease_use_10 +
# tam_perceived_ease_use_12 +
tam_perceived_ease_use_16
computer_attitudes =~
tam_computer_attitudes_6 +
tam_computer_attitudes_7 +
tam_computer_attitudes_8 +
tam_computer_attitudes_14
# tam_computer_attitudes_17
# regressions
computer_attitudes ~ perceived_ease_use + perceived_usefulness + subjective_norms + facilitating_conditions
perceived_ease_use ~ facilitating_conditions
perceived_usefulness ~ subjective_norms + perceived_ease_use
'
m2_1 <- sem(fitmod, data = d, meanstructure = T)
summary(m2_1, fit.measures = TRUE, standardized = TRUE, rsquare = TRUE)## lavaan 0.6-5 ended normally after 49 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 53
##
## Number of observations 249
##
## Model Test User Model:
##
## Test statistic 285.921
## Degrees of freedom 82
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 2119.114
## Degrees of freedom 105
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.899
## Tucker-Lewis Index (TLI) 0.870
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -3555.287
## Loglikelihood unrestricted model (H1) NA
##
## Akaike (AIC) 7216.574
## Bayesian (BIC) 7402.999
## Sample-size adjusted Bayesian (BIC) 7234.986
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.100
## 90 Percent confidence interval - lower 0.087
## 90 Percent confidence interval - upper 0.113
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.056
##
## Parameter Estimates:
##
## Information Expected
## Information saturated (h1) model Structured
## Standard errors Standard
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv
## subjective_norms =~
## tm_sbjctv_nr_2 1.000 0.656
## tm_sbjctv_nr_4 0.894 0.093 9.573 0.000 0.587
## facilitating_conditions =~
## tm_fclttng_c_5 1.000 0.639
## tm_fclttng__13 0.986 0.106 9.309 0.000 0.630
## perceived_usefulness =~
## tm_prcvd_sfl_1 1.000 0.543
## tm_prcvd_sfl_9 1.063 0.087 12.284 0.000 0.577
## tm_prcvd_sf_11 0.870 0.101 8.628 0.000 0.472
## tm_prcvd_sf_15 0.871 0.077 11.349 0.000 0.473
## perceived_ease_use =~
## tm_prcvd_s_s_3 1.000 0.459
## tm_prcvd_s__10 1.600 0.160 10.003 0.000 0.735
## tm_prcvd_s__16 1.435 0.144 9.994 0.000 0.659
## computer_attitudes =~
## tm_cmptr_ttt_6 1.000 0.659
## tm_cmptr_ttt_7 1.115 0.078 14.385 0.000 0.735
## tm_cmptr_ttt_8 1.085 0.076 14.216 0.000 0.715
## tm_cmptr_tt_14 1.082 0.088 12.247 0.000 0.713
## Std.all
##
## 0.841
## 0.736
##
## 0.829
## 0.720
##
## 0.782
## 0.780
## 0.564
## 0.725
##
## 0.635
## 0.817
## 0.816
##
## 0.765
## 0.867
## 0.858
## 0.754
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## computer_attitudes ~
## perceived_es_s 0.702 0.142 4.959 0.000 0.489 0.489
## percevd_sflnss 0.579 0.131 4.420 0.000 0.477 0.477
## subjectiv_nrms -0.073 0.095 -0.764 0.445 -0.072 -0.072
## fclttng_cndtns 0.056 0.091 0.618 0.537 0.054 0.054
## perceived_ease_use ~
## fclttng_cndtns 0.466 0.068 6.805 0.000 0.648 0.648
## perceived_usefulness ~
## subjectiv_nrms 0.471 0.067 7.042 0.000 0.569 0.569
## perceived_es_s 0.460 0.087 5.282 0.000 0.389 0.389
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## subjective_norms ~~
## fclttng_cndtns 0.227 0.039 5.893 0.000 0.542 0.542
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .tm_sbjctv_nr_2 3.952 0.049 79.965 0.000 3.952 5.068
## .tm_sbjctv_nr_4 3.880 0.051 76.757 0.000 3.880 4.864
## .tm_fclttng_c_5 4.032 0.049 82.600 0.000 4.032 5.235
## .tm_fclttng__13 3.593 0.055 64.792 0.000 3.593 4.106
## .tm_prcvd_sfl_1 4.345 0.044 98.827 0.000 4.345 6.263
## .tm_prcvd_sfl_9 4.162 0.047 88.819 0.000 4.162 5.629
## .tm_prcvd_sf_11 3.960 0.053 74.596 0.000 3.960 4.727
## .tm_prcvd_sf_15 4.262 0.041 103.046 0.000 4.262 6.530
## .tm_prcvd_s_s_3 4.153 0.046 90.618 0.000 4.153 5.743
## .tm_prcvd_s__10 3.803 0.057 66.737 0.000 3.803 4.229
## .tm_prcvd_s__16 3.915 0.051 76.466 0.000 3.915 4.846
## .tm_cmptr_ttt_6 4.056 0.055 74.312 0.000 4.056 4.709
## .tm_cmptr_ttt_7 4.057 0.054 75.553 0.000 4.057 4.788
## .tm_cmptr_ttt_8 4.142 0.053 78.438 0.000 4.142 4.971
## .tm_cmptr_tt_14 3.613 0.060 60.220 0.000 3.613 3.816
## subjectiv_nrms 0.000 0.000 0.000
## fclttng_cndtns 0.000 0.000 0.000
## .percevd_sflnss 0.000 0.000 0.000
## .perceived_es_s 0.000 0.000 0.000
## .computer_tttds 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .tm_sbjctv_nr_2 0.178 0.040 4.483 0.000 0.178 0.292
## .tm_sbjctv_nr_4 0.292 0.039 7.413 0.000 0.292 0.459
## .tm_fclttng_c_5 0.185 0.039 4.782 0.000 0.185 0.313
## .tm_fclttng__13 0.369 0.048 7.652 0.000 0.369 0.482
## .tm_prcvd_sfl_1 0.187 0.022 8.359 0.000 0.187 0.388
## .tm_prcvd_sfl_9 0.214 0.025 8.395 0.000 0.214 0.391
## .tm_prcvd_sf_11 0.479 0.046 10.354 0.000 0.479 0.682
## .tm_prcvd_sf_15 0.202 0.022 9.218 0.000 0.202 0.475
## .tm_prcvd_s_s_3 0.312 0.031 9.911 0.000 0.312 0.596
## .tm_prcvd_s__10 0.268 0.037 7.280 0.000 0.268 0.332
## .tm_prcvd_s__16 0.218 0.030 7.320 0.000 0.218 0.334
## .tm_cmptr_ttt_6 0.308 0.032 9.613 0.000 0.308 0.415
## .tm_cmptr_ttt_7 0.178 0.023 7.783 0.000 0.178 0.248
## .tm_cmptr_ttt_8 0.183 0.023 8.054 0.000 0.183 0.264
## .tm_cmptr_tt_14 0.387 0.040 9.723 0.000 0.387 0.432
## subjectiv_nrms 0.430 0.064 6.774 0.000 1.000 1.000
## fclttng_cndtns 0.408 0.061 6.635 0.000 1.000 1.000
## .percevd_sflnss 0.109 0.022 5.050 0.000 0.369 0.369
## .perceived_es_s 0.123 0.026 4.716 0.000 0.581 0.581
## .computer_tttds 0.115 0.022 5.107 0.000 0.264 0.264
##
## R-Square:
## Estimate
## tm_sbjctv_nr_2 0.708
## tm_sbjctv_nr_4 0.541
## tm_fclttng_c_5 0.687
## tm_fclttng__13 0.518
## tm_prcvd_sfl_1 0.612
## tm_prcvd_sfl_9 0.609
## tm_prcvd_sf_11 0.318
## tm_prcvd_sf_15 0.525
## tm_prcvd_s_s_3 0.404
## tm_prcvd_s__10 0.668
## tm_prcvd_s__16 0.666
## tm_cmptr_ttt_6 0.585
## tm_cmptr_ttt_7 0.752
## tm_cmptr_ttt_8 0.736
## tm_cmptr_tt_14 0.568
## percevd_sflnss 0.631
## perceived_es_s 0.419
## computer_tttds 0.736fitmod <- '
# factors
subjective_norms =~
tam_subjective_norm_2 +
tam_subjective_norm_4
facilitating_conditions =~
tam_facilitating_condition_5 +
tam_facilitating_condition_13
perceived_usefulness =~
tam_perceived_usefulness_1 +
tam_perceived_usefulness_9 +
tam_perceived_usefulness_11 +
tam_perceived_usefulness_15
perceived_ease_use =~
tam_perceived_ease_use_3 +
tam_perceived_ease_use_10 +
# tam_perceived_ease_use_12 +
tam_perceived_ease_use_16
computer_attitudes =~
tam_computer_attitudes_6 +
tam_computer_attitudes_7 +
tam_computer_attitudes_8 +
tam_computer_attitudes_14
# tam_computer_attitudes_17
behavioral_intentions =~
intention_use__18 +
intention_use__19
# regressions
computer_attitudes ~ perceived_ease_use + perceived_usefulness + subjective_norms + facilitating_conditions
perceived_ease_use ~ facilitating_conditions
perceived_usefulness ~ subjective_norms + perceived_ease_use
behavioral_intentions ~ computer_attitudes
'
m2_2 <- sem(fitmod, data = d)
summary(m2_2, fit.measures = TRUE, standardized = TRUE, rsquare = TRUE)## lavaan 0.6-5 ended normally after 56 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 43
##
## Number of observations 249
##
## Model Test User Model:
##
## Test statistic 317.981
## Degrees of freedom 110
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 2266.996
## Degrees of freedom 136
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.902
## Tucker-Lewis Index (TLI) 0.879
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -4062.959
## Loglikelihood unrestricted model (H1) NA
##
## Akaike (AIC) 8211.918
## Bayesian (BIC) 8363.168
## Sample-size adjusted Bayesian (BIC) 8226.856
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.087
## 90 Percent confidence interval - lower 0.076
## 90 Percent confidence interval - upper 0.098
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.057
##
## Parameter Estimates:
##
## Information Expected
## Information saturated (h1) model Structured
## Standard errors Standard
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv
## subjective_norms =~
## tm_sbjctv_nr_2 1.000 0.656
## tm_sbjctv_nr_4 0.894 0.093 9.570 0.000 0.586
## facilitating_conditions =~
## tm_fclttng_c_5 1.000 0.639
## tm_fclttng__13 0.986 0.106 9.315 0.000 0.630
## perceived_usefulness =~
## tm_prcvd_sfl_1 1.000 0.543
## tm_prcvd_sfl_9 1.061 0.086 12.275 0.000 0.576
## tm_prcvd_sf_11 0.869 0.101 8.630 0.000 0.472
## tm_prcvd_sf_15 0.871 0.077 11.372 0.000 0.473
## perceived_ease_use =~
## tm_prcvd_s_s_3 1.000 0.459
## tm_prcvd_s__10 1.600 0.160 10.000 0.000 0.735
## tm_prcvd_s__16 1.436 0.144 9.995 0.000 0.660
## computer_attitudes =~
## tm_cmptr_ttt_6 1.000 0.659
## tm_cmptr_ttt_7 1.116 0.077 14.397 0.000 0.735
## tm_cmptr_ttt_8 1.079 0.076 14.142 0.000 0.711
## tm_cmptr_tt_14 1.087 0.088 12.308 0.000 0.716
## behavioral_intentions =~
## intentin_s__18 1.000 0.447
## intentin_s__19 1.635 0.617 2.648 0.008 0.731
## Std.all
##
## 0.841
## 0.735
##
## 0.829
## 0.720
##
## 0.783
## 0.779
## 0.564
## 0.725
##
## 0.635
## 0.817
## 0.816
##
## 0.765
## 0.868
## 0.854
## 0.757
##
## 0.566
## 1.017
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## computer_attitudes ~
## perceived_es_s 0.701 0.141 4.967 0.000 0.488 0.488
## percevd_sflnss 0.579 0.130 4.436 0.000 0.477 0.477
## subjectiv_nrms -0.072 0.095 -0.759 0.448 -0.071 -0.071
## fclttng_cndtns 0.060 0.090 0.662 0.508 0.058 0.058
## perceived_ease_use ~
## fclttng_cndtns 0.465 0.068 6.804 0.000 0.647 0.647
## perceived_usefulness ~
## subjectiv_nrms 0.471 0.067 7.041 0.000 0.569 0.569
## perceived_es_s 0.461 0.087 5.285 0.000 0.390 0.390
## behavioral_intentions ~
## computer_tttds 0.172 0.079 2.172 0.030 0.254 0.254
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## subjective_norms ~~
## fclttng_cndtns 0.227 0.039 5.895 0.000 0.542 0.542
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .tm_sbjctv_nr_2 0.178 0.040 4.476 0.000 0.178 0.292
## .tm_sbjctv_nr_4 0.292 0.039 7.416 0.000 0.292 0.459
## .tm_fclttng_c_5 0.185 0.039 4.780 0.000 0.185 0.312
## .tm_fclttng__13 0.369 0.048 7.660 0.000 0.369 0.482
## .tm_prcvd_sfl_1 0.186 0.022 8.350 0.000 0.186 0.387
## .tm_prcvd_sfl_9 0.215 0.026 8.420 0.000 0.215 0.393
## .tm_prcvd_sf_11 0.479 0.046 10.355 0.000 0.479 0.682
## .tm_prcvd_sf_15 0.202 0.022 9.210 0.000 0.202 0.474
## .tm_prcvd_s_s_3 0.312 0.031 9.914 0.000 0.312 0.597
## .tm_prcvd_s__10 0.269 0.037 7.291 0.000 0.269 0.332
## .tm_prcvd_s__16 0.218 0.030 7.314 0.000 0.218 0.333
## .tm_cmptr_ttt_6 0.308 0.032 9.620 0.000 0.308 0.415
## .tm_cmptr_ttt_7 0.178 0.023 7.789 0.000 0.178 0.247
## .tm_cmptr_ttt_8 0.188 0.023 8.182 0.000 0.188 0.271
## .tm_cmptr_tt_14 0.383 0.040 9.701 0.000 0.383 0.428
## .intentin_s__18 0.424 0.082 5.145 0.000 0.424 0.680
## .intentin_s__19 -0.018 0.195 -0.090 0.928 -0.018 -0.034
## subjectiv_nrms 0.431 0.064 6.775 0.000 1.000 1.000
## fclttng_cndtns 0.408 0.061 6.639 0.000 1.000 1.000
## .percevd_sflnss 0.109 0.022 5.054 0.000 0.369 0.369
## .perceived_es_s 0.122 0.026 4.716 0.000 0.581 0.581
## .computer_tttds 0.113 0.022 5.087 0.000 0.261 0.261
## .behavrl_ntntns 0.187 0.074 2.518 0.012 0.936 0.936
##
## R-Square:
## Estimate
## tm_sbjctv_nr_2 0.708
## tm_sbjctv_nr_4 0.541
## tm_fclttng_c_5 0.688
## tm_fclttng__13 0.518
## tm_prcvd_sfl_1 0.613
## tm_prcvd_sfl_9 0.607
## tm_prcvd_sf_11 0.318
## tm_prcvd_sf_15 0.526
## tm_prcvd_s_s_3 0.403
## tm_prcvd_s__10 0.668
## tm_prcvd_s__16 0.667
## tm_cmptr_ttt_6 0.585
## tm_cmptr_ttt_7 0.753
## tm_cmptr_ttt_8 0.729
## tm_cmptr_tt_14 0.572
## intentin_s__18 0.320
## intentin_s__19 NA
## percevd_sflnss 0.631
## perceived_es_s 0.419
## computer_tttds 0.739
## behavrl_ntntns 0.064fitmod <- '
# factors
computer_attitudes =~
tam_computer_attitudes_6 +
tam_computer_attitudes_7 +
tam_computer_attitudes_8 +
tam_computer_attitudes_14
# tam_computer_attitudes_17
expectancy =~
expectancy_success__20 +
expectancy_success__21 +
expectancy_success__22 +
# expectancy_success__23 +
expectancy_success__24 +
expectancy_success__25
attainment =~
task_value_attainment_value_27 +
task_value_attainment_value_31 +
task_value_attainment_value_33 +
task_value_attainment_value_36 +
task_value_attainment_value_38
interest =~
task_value_interest_value_29 +
task_value_interest_value_32 +
task_value_interest_value_37 +
task_value_interest_value_40
utility =~
task_value_utility_value_28 +
task_value_utility_value_30 +
task_value_utility_value_34 +
task_value_utility_value_35 +
task_value_utility_value_39
task_effort =~
full_cost_task_effort_cost_42 +
full_cost_task_effort_cost_45 +
full_cost_task_effort_cost_46 +
full_cost_task_effort_cost_51 +
full_cost_task_effort_cost_57
outside_effort =~
full_cost_outside_effort_cost_44 +
full_cost_outside_effort_cost_47 +
full_cost_outside_effort_cost_50 +
full_cost_outside_effort_cost_52
lova =~
full_cost_loss_valued_alternatives_43 +
full_cost_loss_valued_alternatives_49 +
full_cost_loss_valued_alternatives_53 +
full_cost_loss_valued_alternatives_56
emotional_costs =~
full_cost_emotional_cost_41 +
full_cost_emotional_cost_48 +
full_cost_emotional_cost_54 +
full_cost_emotional_cost_55 +
full_cost_emotional_cost_58 +
full_cost_emotional_cost_59
behavioral_intentions =~
intention_use__18 +
intention_use__19
# regressions
expectancy ~ computer_attitudes
attainment ~ computer_attitudes
interest ~ computer_attitudes
utility ~ computer_attitudes
task_effort ~ computer_attitudes
outside_effort ~ computer_attitudes
lova ~ computer_attitudes
emotional_costs ~ computer_attitudes
behavioral_intentions ~
expectancy +
attainment +
interest +
utility +
task_effort +
outside_effort +
lova +
emotional_costs
'
m2_3 <- sem(fitmod, data = d)
summary(m2_3, fit.measures = TRUE, standardized = TRUE, rsquare = TRUE)## lavaan 0.6-5 ended normally after 175 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 104
##
## Number of observations 249
##
## Model Test User Model:
##
## Test statistic 3353.701
## Degrees of freedom 886
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 11633.221
## Degrees of freedom 946
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.769
## Tucker-Lewis Index (TLI) 0.753
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -13059.132
## Loglikelihood unrestricted model (H1) NA
##
## Akaike (AIC) 26326.263
## Bayesian (BIC) 26692.079
## Sample-size adjusted Bayesian (BIC) 26362.393
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.106
## 90 Percent confidence interval - lower 0.102
## 90 Percent confidence interval - upper 0.110
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.155
##
## Parameter Estimates:
##
## Information Expected
## Information saturated (h1) model Structured
## Standard errors Standard
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv
## computer_attitudes =~
## tm_cmptr_ttt_6 1.000 0.301
## tm_cmptr_ttt_7 1.225 0.267 4.596 0.000 0.369
## tm_cmptr_ttt_8 1.170 0.258 4.534 0.000 0.352
## tm_cmptr_tt_14 1.580 0.323 4.886 0.000 0.476
## expectancy =~
## expctncy_s__20 1.000 0.480
## expctncy_s__21 1.201 0.133 9.024 0.000 0.577
## expctncy_s__22 0.983 0.112 8.803 0.000 0.472
## expctncy_s__24 1.539 0.152 10.149 0.000 0.740
## expctncy_s__25 1.620 0.158 10.223 0.000 0.778
## attainment =~
## tsk_vl_ttn__27 1.000 0.780
## tsk_vl_ttn__31 1.249 0.087 14.393 0.000 0.974
## tsk_vl_ttn__33 0.712 0.076 9.384 0.000 0.556
## tsk_vl_ttn__36 1.233 0.086 14.278 0.000 0.962
## tsk_vl_ttn__38 1.004 0.077 12.958 0.000 0.783
## interest =~
## tsk_vl_ntr__29 1.000 0.803
## tsk_vl_ntr__32 0.881 0.064 13.767 0.000 0.708
## tsk_vl_ntr__37 0.956 0.067 14.223 0.000 0.768
## tsk_vl_ntr__40 1.054 0.075 14.053 0.000 0.846
## utility =~
## tsk_vl_tlt__28 1.000 0.531
## tsk_vl_tlt__30 1.023 0.103 9.914 0.000 0.543
## tsk_vl_tlt__34 1.204 0.108 11.176 0.000 0.639
## tsk_vl_tlt__35 1.103 0.101 10.969 0.000 0.585
## tsk_vl_tlt__39 0.886 0.097 9.117 0.000 0.471
## task_effort =~
## fll_cst_t___42 1.000 1.578
## fll_cst_t___45 1.018 0.041 24.581 0.000 1.606
## fll_cst_t___46 1.003 0.038 26.620 0.000 1.583
## fll_cst_t___51 0.871 0.047 18.532 0.000 1.375
## fll_cst_t___57 0.934 0.037 24.995 0.000 1.473
## outside_effort =~
## fll_cst_t___44 1.000 1.290
## fll_cst_t___47 1.143 0.072 15.818 0.000 1.474
## fll_cst_t___50 1.155 0.067 17.244 0.000 1.490
## fll_cst_t___52 1.174 0.067 17.423 0.000 1.514
## lova =~
## fll_cst_l___43 1.000 1.188
## fll_cst_l___49 1.200 0.089 13.425 0.000 1.425
## fll_cst_l___53 1.240 0.093 13.348 0.000 1.473
## fll_cst_l___56 1.265 0.089 14.175 0.000 1.503
## emotional_costs =~
## fll_cst_mt__41 1.000 1.316
## fll_cst_mt__48 1.122 0.084 13.348 0.000 1.476
## fll_cst_mt__54 1.166 0.087 13.435 0.000 1.535
## fll_cst_mt__55 1.204 0.089 13.466 0.000 1.585
## fll_cst_mt__58 1.177 0.085 13.813 0.000 1.549
## fll_cst_mt__59 1.243 0.094 13.248 0.000 1.635
## behavioral_intentions =~
## intentin_s__18 1.000 0.431
## intentin_s__19 1.796 0.525 3.419 0.001 0.774
## Std.all
##
## 0.349
## 0.435
## 0.422
## 0.502
##
## 0.686
## 0.661
## 0.642
## 0.764
## 0.772
##
## 0.807
## 0.834
## 0.585
## 0.828
## 0.765
##
## 0.756
## 0.847
## 0.874
## 0.864
##
## 0.637
## 0.749
## 0.891
## 0.862
## 0.673
##
## 0.932
## 0.896
## 0.918
## 0.803
## 0.901
##
## 0.793
## 0.853
## 0.906
## 0.912
##
## 0.709
## 0.866
## 0.861
## 0.914
##
## 0.695
## 0.885
## 0.891
## 0.893
## 0.918
## 0.878
##
## 0.544
## 1.064
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## expectancy ~
## computer_tttds 0.626 0.156 4.010 0.000 0.393 0.393
## attainment ~
## computer_tttds 1.016 0.244 4.167 0.000 0.392 0.392
## interest ~
## computer_tttds 1.279 0.281 4.555 0.000 0.480 0.480
## utility ~
## computer_tttds 0.684 0.170 4.018 0.000 0.388 0.388
## task_effort ~
## computer_tttds -5.139 0.897 -5.729 0.000 -0.981 -0.981
## outside_effort ~
## computer_tttds -4.243 0.761 -5.573 0.000 -0.991 -0.991
## lova ~
## computer_tttds -3.860 0.712 -5.424 0.000 -0.979 -0.979
## emotional_costs ~
## computer_tttds -4.196 0.779 -5.386 0.000 -0.960 -0.960
## behavioral_intentions ~
## expectancy 0.039 0.061 0.631 0.528 0.043 0.043
## attainment -0.083 0.044 -1.875 0.061 -0.149 -0.149
## interest 0.086 0.045 1.905 0.057 0.160 0.160
## utility 0.138 0.068 2.028 0.043 0.170 0.170
## task_effort 0.050 0.113 0.441 0.659 0.182 0.182
## outside_effort -0.175 0.207 -0.842 0.400 -0.523 -0.523
## lova 0.125 0.165 0.758 0.448 0.345 0.345
## emotional_csts -0.038 0.085 -0.448 0.654 -0.117 -0.117
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .tm_cmptr_ttt_6 0.653 0.059 11.118 0.000 0.653 0.878
## .tm_cmptr_ttt_7 0.584 0.053 11.092 0.000 0.584 0.811
## .tm_cmptr_ttt_8 0.572 0.052 11.096 0.000 0.572 0.822
## .tm_cmptr_tt_14 0.672 0.061 11.062 0.000 0.672 0.748
## .expctncy_s__20 0.260 0.028 9.287 0.000 0.260 0.530
## .expctncy_s__21 0.429 0.045 9.526 0.000 0.429 0.563
## .expctncy_s__22 0.317 0.033 9.683 0.000 0.317 0.587
## .expctncy_s__24 0.390 0.048 8.168 0.000 0.390 0.416
## .expctncy_s__25 0.410 0.051 8.016 0.000 0.410 0.404
## .tsk_vl_ttn__27 0.327 0.038 8.614 0.000 0.327 0.349
## .tsk_vl_ttn__31 0.417 0.052 8.036 0.000 0.417 0.305
## .tsk_vl_ttn__33 0.593 0.057 10.464 0.000 0.593 0.658
## .tsk_vl_ttn__36 0.425 0.052 8.170 0.000 0.425 0.315
## .tsk_vl_ttn__38 0.434 0.047 9.239 0.000 0.434 0.414
## .tsk_vl_ntr__29 0.483 0.050 9.683 0.000 0.483 0.428
## .tsk_vl_ntr__32 0.197 0.024 8.279 0.000 0.197 0.282
## .tsk_vl_ntr__37 0.183 0.024 7.486 0.000 0.183 0.237
## .tsk_vl_ntr__40 0.244 0.031 7.818 0.000 0.244 0.254
## .tsk_vl_tlt__28 0.414 0.040 10.365 0.000 0.414 0.595
## .tsk_vl_tlt__30 0.231 0.024 9.643 0.000 0.231 0.439
## .tsk_vl_tlt__34 0.106 0.016 6.441 0.000 0.106 0.206
## .tsk_vl_tlt__35 0.118 0.016 7.528 0.000 0.118 0.256
## .tsk_vl_tlt__39 0.267 0.026 10.188 0.000 0.267 0.546
## .fll_cst_t___42 0.374 0.042 8.953 0.000 0.374 0.131
## .fll_cst_t___45 0.634 0.065 9.834 0.000 0.634 0.197
## .fll_cst_t___46 0.468 0.050 9.398 0.000 0.468 0.157
## .fll_cst_t___51 1.041 0.098 10.575 0.000 1.041 0.355
## .fll_cst_t___57 0.505 0.052 9.757 0.000 0.505 0.189
## .fll_cst_t___44 0.979 0.093 10.542 0.000 0.979 0.370
## .fll_cst_t___47 0.810 0.080 10.157 0.000 0.810 0.272
## .fll_cst_t___50 0.487 0.052 9.351 0.000 0.487 0.180
## .fll_cst_t___52 0.464 0.051 9.177 0.000 0.464 0.168
## .fll_cst_l___43 1.392 0.130 10.695 0.000 1.392 0.497
## .fll_cst_l___49 0.679 0.070 9.717 0.000 0.679 0.251
## .fll_cst_l___53 0.759 0.078 9.785 0.000 0.759 0.259
## .fll_cst_l___56 0.444 0.052 8.535 0.000 0.444 0.164
## .fll_cst_mt__41 1.852 0.171 10.803 0.000 1.852 0.517
## .fll_cst_mt__48 0.604 0.062 9.772 0.000 0.604 0.217
## .fll_cst_mt__54 0.611 0.063 9.676 0.000 0.611 0.206
## .fll_cst_mt__55 0.636 0.066 9.640 0.000 0.636 0.202
## .fll_cst_mt__58 0.449 0.049 9.090 0.000 0.449 0.158
## .fll_cst_mt__59 0.796 0.081 9.869 0.000 0.796 0.229
## .intentin_s__18 0.442 0.065 6.850 0.000 0.442 0.704
## .intentin_s__19 -0.070 0.164 -0.427 0.669 -0.070 -0.133
## computer_tttds 0.091 0.032 2.810 0.005 1.000 1.000
## .expectancy 0.195 0.035 5.639 0.000 0.846 0.846
## .attainment 0.515 0.070 7.306 0.000 0.846 0.846
## .interest 0.496 0.074 6.709 0.000 0.770 0.770
## .utility 0.239 0.045 5.364 0.000 0.849 0.849
## .task_effort 0.095 0.028 3.413 0.001 0.038 0.038
## .outside_effort 0.030 0.020 1.487 0.137 0.018 0.018
## .lova 0.059 0.022 2.636 0.008 0.042 0.042
## .emotional_csts 0.134 0.030 4.478 0.000 0.078 0.078
## .behavrl_ntntns 0.163 0.051 3.165 0.002 0.877 0.877
##
## R-Square:
## Estimate
## tm_cmptr_ttt_6 0.122
## tm_cmptr_ttt_7 0.189
## tm_cmptr_ttt_8 0.178
## tm_cmptr_tt_14 0.252
## expctncy_s__20 0.470
## expctncy_s__21 0.437
## expctncy_s__22 0.413
## expctncy_s__24 0.584
## expctncy_s__25 0.596
## tsk_vl_ttn__27 0.651
## tsk_vl_ttn__31 0.695
## tsk_vl_ttn__33 0.342
## tsk_vl_ttn__36 0.685
## tsk_vl_ttn__38 0.586
## tsk_vl_ntr__29 0.572
## tsk_vl_ntr__32 0.718
## tsk_vl_ntr__37 0.763
## tsk_vl_ntr__40 0.746
## tsk_vl_tlt__28 0.405
## tsk_vl_tlt__30 0.561
## tsk_vl_tlt__34 0.794
## tsk_vl_tlt__35 0.744
## tsk_vl_tlt__39 0.454
## fll_cst_t___42 0.869
## fll_cst_t___45 0.803
## fll_cst_t___46 0.843
## fll_cst_t___51 0.645
## fll_cst_t___57 0.811
## fll_cst_t___44 0.630
## fll_cst_t___47 0.728
## fll_cst_t___50 0.820
## fll_cst_t___52 0.832
## fll_cst_l___43 0.503
## fll_cst_l___49 0.749
## fll_cst_l___53 0.741
## fll_cst_l___56 0.836
## fll_cst_mt__41 0.483
## fll_cst_mt__48 0.783
## fll_cst_mt__54 0.794
## fll_cst_mt__55 0.798
## fll_cst_mt__58 0.842
## fll_cst_mt__59 0.771
## intentin_s__18 0.296
## intentin_s__19 NA
## expectancy 0.154
## attainment 0.154
## interest 0.230
## utility 0.151
## task_effort 0.962
## outside_effort 0.982
## lova 0.958
## emotional_csts 0.922
## behavrl_ntntns 0.123fitmod <- '
# factors
computer_attitudes =~
tam_computer_attitudes_6 +
tam_computer_attitudes_7 +
tam_computer_attitudes_8 +
tam_computer_attitudes_14
# tam_computer_attitudes_17
expectancy =~
expectancy_success__20 +
expectancy_success__21 +
expectancy_success__22 +
# expectancy_success__23 +
expectancy_success__24 +
expectancy_success__25
attainment =~
task_value_attainment_value_27 +
task_value_attainment_value_31 +
task_value_attainment_value_33 +
task_value_attainment_value_36 +
task_value_attainment_value_38
interest =~
task_value_interest_value_29 +
task_value_interest_value_32 +
task_value_interest_value_37 +
task_value_interest_value_40
utility =~
task_value_utility_value_28 +
task_value_utility_value_30 +
task_value_utility_value_34 +
task_value_utility_value_35 +
task_value_utility_value_39
task_effort =~
full_cost_task_effort_cost_42 +
full_cost_task_effort_cost_45 +
full_cost_task_effort_cost_46 +
full_cost_task_effort_cost_51 +
full_cost_task_effort_cost_57
outside_effort =~
full_cost_outside_effort_cost_44 +
full_cost_outside_effort_cost_47 +
full_cost_outside_effort_cost_50 +
full_cost_outside_effort_cost_52
lova =~
full_cost_loss_valued_alternatives_43 +
full_cost_loss_valued_alternatives_49 +
full_cost_loss_valued_alternatives_53 +
full_cost_loss_valued_alternatives_56
emotional_costs =~
full_cost_emotional_cost_41 +
full_cost_emotional_cost_48 +
full_cost_emotional_cost_54 +
full_cost_emotional_cost_55 +
full_cost_emotional_cost_58 +
full_cost_emotional_cost_59
behavioral_intentions =~
intention_use__18 +
intention_use__19
# regressions
computer_attitudes ~ expectancy
computer_attitudes ~ attainment
computer_attitudes ~ interest
computer_attitudes ~ utility
computer_attitudes ~ task_effort
computer_attitudes ~ outside_effort
computer_attitudes ~ lova
computer_attitudes ~ emotional_costs
behavioral_intentions ~ expectancy
behavioral_intentions ~ attainment
behavioral_intentions ~ interest
behavioral_intentions ~ utility
behavioral_intentions ~ task_effort
behavioral_intentions ~ outside_effort
behavioral_intentions ~ lova
behavioral_intentions ~ emotional_costs
behavioral_intentions ~ computer_attitudes
'
m2_4 <- sem(fitmod, data = d)
summary(m2_4, fit.measures = TRUE, standardized = TRUE, rsquare = TRUE)## lavaan 0.6-5 ended normally after 143 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 133
##
## Number of observations 249
##
## Model Test User Model:
##
## Test statistic 2323.911
## Degrees of freedom 857
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 11633.221
## Degrees of freedom 946
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.863
## Tucker-Lewis Index (TLI) 0.848
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -12544.237
## Loglikelihood unrestricted model (H1) NA
##
## Akaike (AIC) 25354.474
## Bayesian (BIC) 25822.295
## Sample-size adjusted Bayesian (BIC) 25400.678
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.083
## 90 Percent confidence interval - lower 0.079
## 90 Percent confidence interval - upper 0.087
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.061
##
## Parameter Estimates:
##
## Information Expected
## Information saturated (h1) model Structured
## Standard errors Standard
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv
## computer_attitudes =~
## tm_cmptr_ttt_6 1.000 0.671
## tm_cmptr_ttt_7 1.126 0.073 15.372 0.000 0.755
## tm_cmptr_ttt_8 1.038 0.073 14.233 0.000 0.696
## tm_cmptr_tt_14 1.056 0.085 12.453 0.000 0.709
## expectancy =~
## expctncy_s__20 1.000 0.488
## expctncy_s__21 1.147 0.127 9.018 0.000 0.560
## expctncy_s__22 0.945 0.107 8.839 0.000 0.461
## expctncy_s__24 1.505 0.144 10.443 0.000 0.735
## expctncy_s__25 1.628 0.151 10.761 0.000 0.795
## attainment =~
## tsk_vl_ttn__27 1.000 0.772
## tsk_vl_ttn__31 1.242 0.087 14.242 0.000 0.958
## tsk_vl_ttn__33 0.762 0.076 10.088 0.000 0.588
## tsk_vl_ttn__36 1.241 0.087 14.335 0.000 0.957
## tsk_vl_ttn__38 1.027 0.078 13.245 0.000 0.793
## interest =~
## tsk_vl_ntr__29 1.000 0.806
## tsk_vl_ntr__32 0.863 0.062 13.950 0.000 0.695
## tsk_vl_ntr__37 0.946 0.065 14.651 0.000 0.762
## tsk_vl_ntr__40 1.071 0.072 14.914 0.000 0.863
## utility =~
## tsk_vl_tlt__28 1.000 0.566
## tsk_vl_tlt__30 0.968 0.090 10.744 0.000 0.548
## tsk_vl_tlt__34 1.111 0.091 12.158 0.000 0.629
## tsk_vl_tlt__35 1.010 0.086 11.788 0.000 0.572
## tsk_vl_tlt__39 0.847 0.086 9.857 0.000 0.480
## task_effort =~
## fll_cst_t___42 1.000 1.575
## fll_cst_t___45 1.010 0.042 23.865 0.000 1.591
## fll_cst_t___46 1.004 0.038 26.449 0.000 1.581
## fll_cst_t___51 0.884 0.046 19.092 0.000 1.393
## fll_cst_t___57 0.939 0.037 25.239 0.000 1.478
## outside_effort =~
## fll_cst_t___44 1.000 1.260
## fll_cst_t___47 1.163 0.076 15.232 0.000 1.465
## fll_cst_t___50 1.191 0.071 16.787 0.000 1.500
## fll_cst_t___52 1.210 0.071 16.952 0.000 1.524
## lova =~
## fll_cst_l___43 1.000 1.186
## fll_cst_l___49 1.191 0.089 13.337 0.000 1.413
## fll_cst_l___53 1.227 0.093 13.218 0.000 1.456
## fll_cst_l___56 1.279 0.089 14.341 0.000 1.518
## emotional_costs =~
## fll_cst_mt__41 1.000 1.311
## fll_cst_mt__48 1.124 0.085 13.263 0.000 1.473
## fll_cst_mt__54 1.169 0.088 13.353 0.000 1.532
## fll_cst_mt__55 1.209 0.090 13.405 0.000 1.585
## fll_cst_mt__58 1.185 0.086 13.789 0.000 1.554
## fll_cst_mt__59 1.247 0.095 13.184 0.000 1.634
## behavioral_intentions =~
## intentin_s__18 1.000 0.438
## intentin_s__19 1.701 0.511 3.328 0.001 0.745
## Std.all
##
## 0.778
## 0.890
## 0.834
## 0.748
##
## 0.697
## 0.642
## 0.628
## 0.759
## 0.789
##
## 0.798
## 0.820
## 0.619
## 0.824
## 0.775
##
## 0.759
## 0.832
## 0.867
## 0.880
##
## 0.679
## 0.756
## 0.877
## 0.843
## 0.687
##
## 0.930
## 0.887
## 0.916
## 0.814
## 0.904
##
## 0.775
## 0.848
## 0.912
## 0.918
##
## 0.709
## 0.858
## 0.851
## 0.923
##
## 0.692
## 0.883
## 0.890
## 0.893
## 0.921
## 0.877
##
## 0.555
## 1.037
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## computer_attitudes ~
## expectancy -0.068 0.091 -0.744 0.457 -0.049 -0.049
## attainment -0.111 0.090 -1.228 0.219 -0.128 -0.128
## interest 0.870 0.114 7.613 0.000 1.044 1.044
## utility -0.165 0.094 -1.747 0.081 -0.139 -0.139
## task_effort 0.158 0.280 0.565 0.572 0.372 0.372
## outside_effort -0.151 0.383 -0.396 0.692 -0.284 -0.284
## lova 0.113 0.240 0.469 0.639 0.199 0.199
## emotional_csts -0.213 0.167 -1.278 0.201 -0.416 -0.416
## behavioral_intentions ~
## expectancy 0.056 0.086 0.642 0.521 0.062 0.062
## attainment -0.133 0.095 -1.401 0.161 -0.234 -0.234
## interest 0.045 0.154 0.291 0.771 0.083 0.083
## utility 0.173 0.105 1.645 0.100 0.224 0.224
## task_effort -0.215 0.269 -0.802 0.423 -0.774 -0.774
## outside_effort 0.264 0.368 0.719 0.472 0.760 0.760
## lova -0.097 0.229 -0.423 0.672 -0.263 -0.263
## emotional_csts 0.057 0.157 0.364 0.716 0.171 0.171
## computer_tttds 0.072 0.131 0.548 0.584 0.110 0.110
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## expectancy ~~
## attainment 0.215 0.035 6.085 0.000 0.570 0.570
## interest 0.217 0.037 5.934 0.000 0.552 0.552
## utility 0.157 0.027 5.801 0.000 0.567 0.567
## task_effort -0.264 0.060 -4.422 0.000 -0.344 -0.344
## outside_effort -0.224 0.050 -4.496 0.000 -0.364 -0.364
## lova -0.230 0.049 -4.711 0.000 -0.396 -0.396
## emotional_csts -0.229 0.052 -4.395 0.000 -0.358 -0.358
## attainment ~~
## interest 0.512 0.065 7.862 0.000 0.824 0.824
## utility 0.292 0.043 6.723 0.000 0.668 0.668
## task_effort -0.394 0.089 -4.407 0.000 -0.324 -0.324
## outside_effort -0.316 0.074 -4.295 0.000 -0.325 -0.325
## lova -0.364 0.074 -4.957 0.000 -0.398 -0.398
## emotional_csts -0.363 0.079 -4.603 0.000 -0.359 -0.359
## interest ~~
## utility 0.320 0.047 6.814 0.000 0.702 0.702
## task_effort -0.514 0.097 -5.314 0.000 -0.405 -0.405
## outside_effort -0.411 0.080 -5.129 0.000 -0.405 -0.405
## lova -0.464 0.081 -5.690 0.000 -0.485 -0.485
## emotional_csts -0.467 0.087 -5.365 0.000 -0.442 -0.442
## utility ~~
## task_effort -0.315 0.068 -4.625 0.000 -0.353 -0.353
## outside_effort -0.261 0.057 -4.611 0.000 -0.365 -0.365
## lova -0.255 0.055 -4.650 0.000 -0.379 -0.379
## emotional_csts -0.243 0.058 -4.203 0.000 -0.328 -0.328
## task_effort ~~
## outside_effort 1.984 0.212 9.368 0.000 1.000 1.000
## lova 1.767 0.204 8.659 0.000 0.946 0.946
## emotional_csts 1.961 0.229 8.558 0.000 0.950 0.950
## outside_effort ~~
## lova 1.452 0.179 8.121 0.000 0.971 0.971
## emotional_csts 1.545 0.195 7.931 0.000 0.935 0.935
## lova ~~
## emotional_csts 1.497 0.195 7.663 0.000 0.963 0.963
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .tm_cmptr_ttt_6 0.293 0.031 9.621 0.000 0.293 0.395
## .tm_cmptr_ttt_7 0.150 0.021 7.282 0.000 0.150 0.208
## .tm_cmptr_ttt_8 0.212 0.024 8.832 0.000 0.212 0.304
## .tm_cmptr_tt_14 0.396 0.040 9.893 0.000 0.396 0.441
## .expctncy_s__20 0.253 0.027 9.350 0.000 0.253 0.515
## .expctncy_s__21 0.448 0.046 9.823 0.000 0.448 0.588
## .expctncy_s__22 0.327 0.033 9.919 0.000 0.327 0.606
## .expctncy_s__24 0.397 0.047 8.534 0.000 0.397 0.424
## .expctncy_s__25 0.384 0.048 7.979 0.000 0.384 0.378
## .tsk_vl_ttn__27 0.340 0.037 9.178 0.000 0.340 0.364
## .tsk_vl_ttn__31 0.448 0.051 8.830 0.000 0.448 0.328
## .tsk_vl_ttn__33 0.555 0.053 10.463 0.000 0.555 0.616
## .tsk_vl_ttn__36 0.433 0.049 8.754 0.000 0.433 0.321
## .tsk_vl_ttn__38 0.419 0.044 9.464 0.000 0.419 0.400
## .tsk_vl_ntr__29 0.479 0.047 10.162 0.000 0.479 0.424
## .tsk_vl_ntr__32 0.214 0.023 9.480 0.000 0.214 0.307
## .tsk_vl_ntr__37 0.192 0.022 8.876 0.000 0.192 0.248
## .tsk_vl_ntr__40 0.216 0.025 8.554 0.000 0.216 0.225
## .tsk_vl_tlt__28 0.375 0.037 10.198 0.000 0.375 0.539
## .tsk_vl_tlt__30 0.225 0.023 9.648 0.000 0.225 0.428
## .tsk_vl_tlt__34 0.119 0.016 7.339 0.000 0.119 0.231
## .tsk_vl_tlt__35 0.134 0.016 8.331 0.000 0.134 0.290
## .tsk_vl_tlt__39 0.258 0.025 10.157 0.000 0.258 0.528
## .fll_cst_t___42 0.385 0.041 9.427 0.000 0.385 0.134
## .fll_cst_t___45 0.684 0.067 10.206 0.000 0.684 0.213
## .fll_cst_t___46 0.476 0.049 9.777 0.000 0.476 0.160
## .fll_cst_t___51 0.992 0.093 10.667 0.000 0.992 0.338
## .fll_cst_t___57 0.491 0.049 10.002 0.000 0.491 0.184
## .fll_cst_t___44 1.055 0.097 10.827 0.000 1.055 0.399
## .fll_cst_t___47 0.837 0.079 10.541 0.000 0.837 0.280
## .fll_cst_t___50 0.457 0.047 9.753 0.000 0.457 0.169
## .fll_cst_t___52 0.433 0.045 9.582 0.000 0.433 0.157
## .fll_cst_l___43 1.395 0.130 10.761 0.000 1.395 0.498
## .fll_cst_l___49 0.713 0.071 9.980 0.000 0.713 0.263
## .fll_cst_l___53 0.809 0.080 10.063 0.000 0.809 0.276
## .fll_cst_l___56 0.399 0.047 8.413 0.000 0.399 0.148
## .fll_cst_mt__41 1.865 0.172 10.833 0.000 1.865 0.521
## .fll_cst_mt__48 0.613 0.062 9.889 0.000 0.613 0.220
## .fll_cst_mt__54 0.619 0.063 9.799 0.000 0.619 0.209
## .fll_cst_mt__55 0.636 0.065 9.741 0.000 0.636 0.202
## .fll_cst_mt__58 0.432 0.047 9.136 0.000 0.432 0.152
## .fll_cst_mt__59 0.798 0.080 9.961 0.000 0.798 0.230
## .intentin_s__18 0.432 0.067 6.450 0.000 0.432 0.692
## .intentin_s__19 -0.039 0.158 -0.248 0.804 -0.039 -0.076
## .computer_tttds 0.094 0.021 4.486 0.000 0.210 0.210
## expectancy 0.238 0.041 5.883 0.000 1.000 1.000
## attainment 0.595 0.081 7.358 0.000 1.000 1.000
## interest 0.649 0.094 6.937 0.000 1.000 1.000
## utility 0.321 0.055 5.877 0.000 1.000 1.000
## task_effort 2.480 0.255 9.712 0.000 1.000 1.000
## outside_effort 1.588 0.218 7.270 0.000 1.000 1.000
## lova 1.407 0.221 6.382 0.000 1.000 1.000
## emotional_csts 1.718 0.277 6.196 0.000 1.000 1.000
## .behavrl_ntntns 0.174 0.058 3.024 0.002 0.906 0.906
##
## R-Square:
## Estimate
## tm_cmptr_ttt_6 0.605
## tm_cmptr_ttt_7 0.792
## tm_cmptr_ttt_8 0.696
## tm_cmptr_tt_14 0.559
## expctncy_s__20 0.485
## expctncy_s__21 0.412
## expctncy_s__22 0.394
## expctncy_s__24 0.576
## expctncy_s__25 0.622
## tsk_vl_ttn__27 0.636
## tsk_vl_ttn__31 0.672
## tsk_vl_ttn__33 0.384
## tsk_vl_ttn__36 0.679
## tsk_vl_ttn__38 0.600
## tsk_vl_ntr__29 0.576
## tsk_vl_ntr__32 0.693
## tsk_vl_ntr__37 0.752
## tsk_vl_ntr__40 0.775
## tsk_vl_tlt__28 0.461
## tsk_vl_tlt__30 0.572
## tsk_vl_tlt__34 0.769
## tsk_vl_tlt__35 0.710
## tsk_vl_tlt__39 0.472
## fll_cst_t___42 0.866
## fll_cst_t___45 0.787
## fll_cst_t___46 0.840
## fll_cst_t___51 0.662
## fll_cst_t___57 0.816
## fll_cst_t___44 0.601
## fll_cst_t___47 0.720
## fll_cst_t___50 0.831
## fll_cst_t___52 0.843
## fll_cst_l___43 0.502
## fll_cst_l___49 0.737
## fll_cst_l___53 0.724
## fll_cst_l___56 0.852
## fll_cst_mt__41 0.479
## fll_cst_mt__48 0.780
## fll_cst_mt__54 0.791
## fll_cst_mt__55 0.798
## fll_cst_mt__58 0.848
## fll_cst_mt__59 0.770
## intentin_s__18 0.308
## intentin_s__19 NA
## computer_tttds 0.790
## behavrl_ntntns 0.094