## [1] "ID" "Condition"
## [3] "Site" "Coach"
## [5] "Session" "Morn_Aft"
## [7] "Day" "Age_month"
## [9] "Waist_Circumference_cm" "BMI"
## [11] "OrgSport" "MVPA_ATHLETE_EV"
## [13] "Min_MVPA_Ath_EV" "VPA_ATHLETE_EV"
## [15] "Min_VPA_Ath_EV" "MPA_ATHLETE_EV"
## [17] "Min_MPA_Ath_EV" "SED_ATHLETE_EV"
## [19] "Min_SED_Ath_EV" "MVPA_COACH_TRO"
## [21] "MIN_MVPA_COACH_TRO" "VPA_COACH_TRO"
## [23] "MIN_VPA_COACH_TRO" "MPA_COACH_TRO"
## [25] "MIN_MPA_COACH_TRO" "SED_COACH_TRO"
## [27] "MIN_SED_COACH_TRO" "Management"
## [29] "Knowledge" "Promo_PA"
## [31] "Demo_PA" "Dis"
## [33] "MVPA_EV_CHANGE" "VPA_EV_CHANGE"
## [35] "MPA_EV_CHANGE" "SED_EV_CHANGE"
## [37] "MVPA_COACH_TRO_CHANGE" "VPA_COACH_TRO_CHANGE"
## [39] "MPA_COACH_TRO_CHANGE" "SED_COACH_TRO_CHANGE"
## [41] "Management_change" "Knowledge_change"
## [43] "Promo_PA_change" "Demo_PA_change"
## [45] "Dis_change" "Man_Knowl_change"
## Compare linear to quadratic
## Data: dataExclude
## Models:
## TE_base: SED_ATHLETE_EV ~ Condition + baseline + Condition:baseline +
## TE_base: Session + (1 | ID) + (1 | Coach) + (1 | Site)
## TE: SED_ATHLETE_EV ~ Condition + baseline + Condition:baseline +
## TE: Session + I(Session^2) + (1 | ID) + (1 | Coach) + (1 | Site)
## Df AIC BIC logLik deviance Chisq Chi Df Pr(>Chisq)
## TE_base 9 4054 4093 -2018 4036
## TE 10 4056 4099 -2018 4036 0.02 1 0.87
## Compare baseline vs session as treatment variable of interest
## Data: dataExclude
## Models:
## TE: SED_ATHLETE_EV ~ Condition + baseline + Condition:baseline +
## TE: Session + I(Session^2) + (1 | ID) + (1 | Coach) + (1 | Site)
## TE_1: SED_ATHLETE_EV ~ Condition + baseline + Session + I(Session^2) +
## TE_1: (1 | ID) + (1 | Coach) + (1 | Site) + Condition:baseline +
## TE_1: Condition:Session
## TE_2: SED_ATHLETE_EV ~ Condition + baseline + Session + I(Session^2) +
## TE_2: (1 | ID) + (1 | Coach) + (1 | Site) + Condition:baseline +
## TE_2: Condition:Session + Condition:baseline:Session
## Df AIC BIC logLik deviance Chisq Chi Df Pr(>Chisq)
## TE 10 4056 4099 -2018 4036
## TE_1 11 4058 4106 -2018 4036 0.00 1 0.974
## TE_2 12 4055 4108 -2016 4031 4.26 1 0.039 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: dataExclude
## Models:
## TE: SED_ATHLETE_EV ~ Condition + baseline + Condition:baseline +
## TE: Session + I(Session^2) + (1 | ID) + (1 | Coach) + (1 | Site)
## TE_2: SED_ATHLETE_EV ~ Condition + baseline + Session + I(Session^2) +
## TE_2: (1 | ID) + (1 | Coach) + (1 | Site) + Condition:baseline +
## TE_2: Condition:Session + Condition:baseline:Session
## Df AIC BIC logLik deviance Chisq Chi Df Pr(>Chisq)
## TE 10 4056 4099 -2018 4036
## TE_2 12 4055 4108 -2016 4031 4.26 2 0.12
I will using quasi-bayes simulation for confidence intervals (see Galman and Hills, 2008)
## (Intercept) Condition baseline
## 51.14718 -0.11501 -19.41472
## Session I(Session^2) Condition:baseline
## 0.80803 -0.01337 14.72560
## Confidence Intervals
## -----------------------------------
## 0.5% 2.5% 97.5% 99.5%
## (Intercept) 36.6014 39.5664 62.8759 65.6872
## Condition -4.1679 -3.1419 2.8163 4.1384
## baseline -28.3906 -25.6437 -13.5781 -12.2168
## Session -2.0655 -1.4535 3.2241 4.3662
## I(Session^2) -0.2486 -0.1772 0.1485 0.1862
## Condition:baseline 10.1815 11.1750 18.5407 19.8123
## (Intercept) Condition baseline
## 42.875999 -0.074098 -17.344277
## Session I(Session^2) Management
## -0.086658 0.026983 -0.147966
## Knowledge Dis SED_COACH_TRO
## 0.001949 -1.122954 0.228105
## Condition:baseline
## 12.183030
## Confidence Intervals
## -----------------------------------
## 0.5% 2.5% 97.5% 99.5%
## (Intercept) 27.0484 30.3238 55.71266 60.4530
## Condition -3.8638 -2.6503 2.76559 3.4361
## baseline -27.5232 -25.3993 -9.68731 -7.5609
## Session -3.6032 -2.6015 2.42261 3.5341
## I(Session^2) -0.1936 -0.1477 0.19838 0.2594
## Management -0.4982 -0.4189 0.12477 0.1818
## Knowledge -0.1536 -0.1181 0.11958 0.1429
## Dis -3.0188 -2.4803 0.05013 0.4212
## SED_COACH_TRO 0.1194 0.1416 0.31266 0.3369
## Condition:baseline 7.1942 8.1855 16.05049 17.3576
## Total IE
## Point Estimate: 2.679
## CIs: -4.691 -2.692 8.087 9.558
## Graph of density of estimated Total indirect effect
## -------------------------------
Done equation by equation - equivilent to seemingly unrelated regression
## Results: Mangement
## -----------------------
## (Intercept) Condition baseline
## 16.8011 0.2496 -9.4605
## Session Condition:baseline
## 0.2889 6.5941
## Confidence Intervals
## -----------------------------------
## 0.5% 2.5% 97.5% 99.5%
## (Intercept) 14.5638 15.1988 18.2758 18.7895
## Condition -0.7886 -0.4889 1.0636 1.2305
## baseline -10.8211 -10.5069 -8.2334 -7.8659
## Session 0.1129 0.1587 0.4176 0.4416
## Condition:baseline 4.8081 5.1947 7.7034 8.1999
## Results: Knowledge
## -----------------------
## (Intercept) Condition baseline
## 22.87447 1.24676 -6.73186
## Session Condition:baseline
## 0.04335 5.53330
## Confidence Intervals
## -----------------------------------
## 0.5% 2.5% 97.5% 99.5%
## (Intercept) 15.3873 17.2600 28.3557 29.4460
## Condition -0.8900 -0.5504 3.0116 3.5212
## baseline -10.0134 -8.9378 -4.4154 -3.4621
## Session -0.3121 -0.2405 0.3248 0.4291
## Condition:baseline 1.9484 2.7698 8.3668 9.2225
## Results: Dis
## -----------------------
## (Intercept) Condition baseline
## 1.07787 0.09684 -1.15619
## Session Condition:baseline
## 0.02731 -0.06757
## Confidence Intervals
## -----------------------------------
## 0.5% 2.5% 97.5% 99.5%
## (Intercept) 0.819848 0.861771 1.27629 1.33487
## Condition -0.118221 -0.054685 0.25995 0.31454
## baseline -1.461327 -1.372760 -0.93233 -0.88132
## Session -0.006849 0.001881 0.05285 0.05922
## Condition:baseline -0.382218 -0.301792 0.15986 0.22481
## Results: SED_COACH_TRO
## -----------------------
## (Intercept) Condition baseline
## 55.6936 0.4943 -14.8166
## Session Condition:baseline
## 1.6380 14.2173
## Confidence Intervals
## -----------------------------------
## 0.5% 2.5% 97.5% 99.5%
## (Intercept) 45.607 47.398 63.483 65.802
## Condition -2.287 -1.673 2.751 3.453
## baseline -19.236 -18.158 -11.630 -10.605
## Session 1.143 1.266 2.026 2.179
## Condition:baseline 8.872 10.741 18.045 18.951
## Results: SED_ATHLETE_EV
## -----------------------
## (Intercept) baseline Management
## 42.715355 -18.370020 -0.162448
## Knowledge Dis SED_COACH_TRO
## 0.001463 -1.135643 0.226357
## Session Condition baseline:Condition
## 0.316537 -0.067838 12.304090
## Confidence Intervals
## -----------------------------------
## 0.5% 2.5% 97.5% 99.5%
## (Intercept) 25.3035 29.6512 54.39401 58.5285
## baseline -23.4250 -22.3592 -14.24746 -12.9197
## Management -0.5093 -0.4125 0.08711 0.1920
## Knowledge -0.1476 -0.1174 0.12246 0.1493
## Dis -2.7303 -2.3817 0.24279 0.6423
## SED_COACH_TRO 0.1132 0.1385 0.30907 0.3358
## Session -0.2367 -0.1078 0.74555 0.8606
## Condition -3.6621 -2.7889 2.84421 3.9697
## baseline:Condition 6.7803 8.1069 16.28298 17.3703
Again all done via Quasi-bayes
## Management
## Point Estimate: -1.061
## CIs: -3.462 -2.819 0.5405 1.307
## Knowledge
## Point Estimate: -0.004207
## CIs: -1.095 -0.7027 0.7344 0.9881
## Dis
## Point Estimate: 0.06947
## CIs: -0.4034 -0.2281 0.441 0.6086
## SED_COACH_TRO
## Point Estimate: 3.203
## CIs: 1.611 1.861 4.695 5.206
## Total Indirect Effect:
## Total IE
## Point Estimate: 2.207
## CIs: -0.781 0.1646 4.348 5.052
## Graph of density of estimated Total indirect effect
## -------------------------------