Month?
Jonathan Spiess
May 7, 2021
Overview
I need to do a few things with month, and the last one keeps putting me on a fun loop of repeating the same thing over and over.
1: Look for differences in TSF, ESD, or Grazer Type across seasons and years Solution: Fully nested random effect (1|Location/Month/Year)
2: Look for differences in TSF, ESD, or Grazer Type over individual grazing seasons Solution: (1|Location/Month) random effect for individual seasons
3: Look at within season variability for individual grazing seasons Current solution: separate model selection using (1|Location) as the random effect to test TSF*Month
Is a null comparison and single term model comparisons enough to say the TSF*Month interaction is important and look at the graph/describe trends for that year?
(I can leave it there...or look at TSF differences for each month subset and then month differences for each TSF subset. You and Caley both have said this part seems excessive for now, so not actually planning on doing this at the moment.)
KgHa Example Graph
KgHa Overall Models
TSF is best single term model
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular## Data: HRECSIOmit
## Models:
## KgHaNull: log(KgHa + 1) ~ 1 + (1 | Location/Month/Year)
## KgHaG: log(KgHa + 1) ~ Treatment + (1 | Location/Month/Year)
## KgHaT: log(KgHa + 1) ~ TSF + (1 | Location/Month/Year)
## KgHaE: log(KgHa + 1) ~ ESD + (1 | Location/Month/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaNull 5 4031.2 4059.2 -2010.6 4021.2
## KgHaG 6 4032.3 4065.9 -2010.2 4020.3 0.8545 1 0.3553
## KgHaT 9 3663.1 3713.5 -1822.6 3645.1 375.2253 3 <2e-16 ***
## KgHaE 9 3990.3 4040.7 -1986.2 3972.3 0.0000 0
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECSIOmit
## Models:
## KgHaNull: log(KgHa + 1) ~ 1 + (1 | Location/Month/Year)
## KgHaT: log(KgHa + 1) ~ TSF + (1 | Location/Month/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaNull 5 4031.2 4059.2 -2010.6 4021.2
## KgHaT 9 3663.1 3713.5 -1822.6 3645.1 376.08 4 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECSIOmit
## Models:
## KgHaNull: log(KgHa + 1) ~ 1 + (1 | Location/Month/Year)
## KgHaG: log(KgHa + 1) ~ Treatment + (1 | Location/Month/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaNull 5 4031.2 4059.2 -2010.6 4021.2
## KgHaG 6 4032.3 4065.9 -2010.2 4020.3 0.8545 1 0.3553## Data: HRECSIOmit
## Models:
## KgHaNull: log(KgHa + 1) ~ 1 + (1 | Location/Month/Year)
## KgHaE: log(KgHa + 1) ~ ESD + (1 | Location/Month/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaNull 5 4031.2 4059.2 -2010.6 4021.2
## KgHaE 9 3990.3 4040.7 -1986.2 3972.3 48.909 4 6.099e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(KgHa + 1) ~ TSF + (1 | Location/Month/Year),
## data = HRECSIOmit, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1to2 - RB == 0 0.54567 0.03934 13.871 < 0.001 ***
## 2to3 - RB == 0 0.70380 0.04565 15.418 < 0.001 ***
## 3plus - RB == 0 0.78886 0.05974 13.205 < 0.001 ***
## NYB - RB == 0 0.52298 0.03624 14.429 < 0.001 ***
## 2to3 - 1to2 == 0 0.15813 0.04682 3.378 0.00633 **
## 3plus - 1to2 == 0 0.24319 0.06053 4.018 < 0.001 ***
## NYB - 1to2 == 0 -0.02269 0.04078 -0.556 0.98029
## 3plus - 2to3 == 0 0.08507 0.06245 1.362 0.64220
## NYB - 2to3 == 0 -0.18081 0.04869 -3.713 0.00181 **
## NYB - 3plus == 0 -0.26588 0.06364 -4.178 < 0.001 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(KgHa + 1) ~ Treatment + (1 | Location/Month/Year),
## data = HRECSIOmit, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 -0.1088 0.1135 -0.959 0.338
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(KgHa + 1) ~ ESD + (1 | Location/Month/Year),
## data = HRECSIOmit, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Loamy - Clayey == 0 0.06305 0.06051 1.042 0.81676
## Saline Lowland - Clayey == 0 -0.09777 0.04466 -2.189 0.16194
## Sandy - Clayey == 0 -0.20672 0.04205 -4.916 < 0.001 ***
## Thin Claypan - Clayey == 0 -0.45591 0.12277 -3.714 0.00147 **
## Saline Lowland - Loamy == 0 -0.16081 0.06019 -2.672 0.04961 *
## Sandy - Loamy == 0 -0.26976 0.05316 -5.075 < 0.001 ***
## Thin Claypan - Loamy == 0 -0.51896 0.12826 -4.046 < 0.001 ***
## Sandy - Saline Lowland == 0 -0.10895 0.03656 -2.980 0.02004 *
## Thin Claypan - Saline Lowland == 0 -0.35815 0.11742 -3.050 0.01605 *
## Thin Claypan - Sandy == 0 -0.24920 0.11819 -2.109 0.19226
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)KgHa Over Individual Seasons
Shortened to 2017, this is the same as what we did for the drought paper
##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(KgHa + 1) ~ TSF + (1 | Location/Month), data = subset(HRECSIOmit17,
## Treatment == "Cattle"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## NYB - RB == 0 0.67086 0.08263 8.119 4.44e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(KgHa + 1) ~ TSF + (1 | Location/Month), data = subset(HRECSIOmit17,
## Treatment == "Sheep"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## NYB - RB == 0 0.21208 0.08145 2.604 0.00922 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)KgHa TSF*Month Interaction Test 2017
For 2017, it seems TSF alone was better/equal to the TSF*Month model
## Data: subset(HRECSIOmit17, Treatment == "Cattle")
## Models:
## KgHaMTnullc: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTtsfc: log(KgHa + 1) ~ TSF + (1 | Location)
## KgHaMTmonthc: log(KgHa + 1) ~ Month + (1 | Location)
## KgHaMTesdc: log(KgHa + 1) ~ ESD + (1 | Location)
## KgHaMTtmic: log(KgHa + 1) ~ TSF * Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnullc 3 357.27 367.13 -175.63 351.27
## KgHaMTtsfc 4 303.50 316.65 -147.75 295.50 55.769 1 8.149e-14 ***
## KgHaMTmonthc 5 357.09 373.53 -173.54 347.09 0.000 1 1
## KgHaMTesdc 6 360.59 380.32 -174.30 348.59 0.000 1 1
## KgHaMTtmic 8 303.52 329.83 -143.76 287.52 61.074 2 5.469e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit17, Treatment == "Cattle")
## Models:
## KgHaMTnullc: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTtsfc: log(KgHa + 1) ~ TSF + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnullc 3 357.27 367.13 -175.63 351.27
## KgHaMTtsfc 4 303.50 316.65 -147.75 295.50 55.769 1 8.149e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit17, Treatment == "Cattle")
## Models:
## KgHaMTnullc: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTmonthc: log(KgHa + 1) ~ Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnullc 3 357.27 367.13 -175.63 351.27
## KgHaMTmonthc 5 357.09 373.53 -173.54 347.09 4.1782 2 0.1238## Data: subset(HRECSIOmit17, Treatment == "Cattle")
## Models:
## KgHaMTnullc: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTesdc: log(KgHa + 1) ~ ESD + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnullc 3 357.27 367.13 -175.63 351.27
## KgHaMTesdc 6 360.59 380.32 -174.30 348.59 2.6713 3 0.4451## Data: subset(HRECSIOmit17, Treatment == "Cattle")
## Models:
## KgHaMTnullc: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTtmic: log(KgHa + 1) ~ TSF * Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnullc 3 357.27 367.13 -175.63 351.27
## KgHaMTtmic 8 303.52 329.83 -143.76 287.52 63.745 5 2.04e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit17, Treatment == "Cattle")
## Models:
## KgHaMTtsfc: log(KgHa + 1) ~ TSF + (1 | Location)
## KgHaMTtmic: log(KgHa + 1) ~ TSF * Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTtsfc 4 303.50 316.65 -147.75 295.50
## KgHaMTtmic 8 303.52 329.83 -143.76 287.52 7.976 4 0.09246 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit17, Treatment == "Sheep")
## Models:
## KgHaMTnulls: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTtsfs: log(KgHa + 1) ~ TSF + (1 | Location)
## KgHaMTmonths: log(KgHa + 1) ~ Month + (1 | Location)
## KgHaMTesds: log(KgHa + 1) ~ ESD + (1 | Location)
## KgHaMTtmis: log(KgHa + 1) ~ TSF * Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnulls 3 278.95 288.68 -136.47 272.95
## KgHaMTtsfs 4 274.43 287.40 -133.22 266.43 6.5216 1 0.01066 *
## KgHaMTmonths 5 278.58 294.79 -134.29 268.58 0.0000 1 1.00000
## KgHaMTesds 7 275.31 298.00 -130.65 261.31 7.2722 2 0.02635 *
## KgHaMTtmis 8 277.87 303.80 -130.93 261.87 0.0000 1 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit17, Treatment == "Sheep")
## Models:
## KgHaMTnulls: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTtsfs: log(KgHa + 1) ~ TSF + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnulls 3 278.95 288.68 -136.47 272.95
## KgHaMTtsfs 4 274.43 287.40 -133.22 266.43 6.5216 1 0.01066 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit17, Treatment == "Sheep")
## Models:
## KgHaMTnulls: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTmonths: log(KgHa + 1) ~ Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnulls 3 278.95 288.68 -136.47 272.95
## KgHaMTmonths 5 278.58 294.79 -134.29 268.58 4.3727 2 0.1123## Data: subset(HRECSIOmit17, Treatment == "Sheep")
## Models:
## KgHaMTnulls: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTesds: log(KgHa + 1) ~ ESD + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnulls 3 278.95 288.68 -136.47 272.95
## KgHaMTesds 7 275.31 298.00 -130.65 261.31 11.645 4 0.0202 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit17, Treatment == "Sheep")
## Models:
## KgHaMTnulls: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTtmis: log(KgHa + 1) ~ TSF * Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnulls 3 278.95 288.68 -136.47 272.95
## KgHaMTtmis 8 277.87 303.80 -130.93 261.87 11.082 5 0.04978 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit17, Treatment == "Sheep")
## Models:
## KgHaMTtsfs: log(KgHa + 1) ~ TSF + (1 | Location)
## KgHaMTtmis: log(KgHa + 1) ~ TSF * Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTtsfs 4 274.43 287.4 -133.22 266.43
## KgHaMTtmis 8 277.87 303.8 -130.93 261.87 4.5603 4 0.3355KgHa TSF*Month Interaction Test 2018
Same thing for 2018.
I probably should have done this for ammonium or nitrate as the example, but will update with that in a bit
## Data: subset(HRECSIOmit17, Treatment == "Cattle")
## Models:
## KgHaMTnullc18: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTtsfc18: log(KgHa + 1) ~ TSF + (1 | Location)
## KgHaMTmonthc18: log(KgHa + 1) ~ Month + (1 | Location)
## KgHaMTesdc18: log(KgHa + 1) ~ ESD + (1 | Location)
## KgHaMTtmic18: log(KgHa + 1) ~ TSF * Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnullc18 3 357.27 367.13 -175.63 351.27
## KgHaMTtsfc18 4 303.50 316.65 -147.75 295.50 55.769 1 8.149e-14 ***
## KgHaMTmonthc18 5 357.09 373.53 -173.54 347.09 0.000 1 1
## KgHaMTesdc18 6 360.59 380.32 -174.30 348.59 0.000 1 1
## KgHaMTtmic18 8 303.52 329.83 -143.76 287.52 61.074 2 5.469e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit17, Treatment == "Cattle")
## Models:
## KgHaMTnullc18: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTtsfc18: log(KgHa + 1) ~ TSF + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnullc18 3 357.27 367.13 -175.63 351.27
## KgHaMTtsfc18 4 303.50 316.65 -147.75 295.50 55.769 1 8.149e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit17, Treatment == "Cattle")
## Models:
## KgHaMTnullc18: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTmonthc18: log(KgHa + 1) ~ Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnullc18 3 357.27 367.13 -175.63 351.27
## KgHaMTmonthc18 5 357.09 373.53 -173.54 347.09 4.1782 2 0.1238## Data: subset(HRECSIOmit17, Treatment == "Cattle")
## Models:
## KgHaMTnullc18: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTesdc18: log(KgHa + 1) ~ ESD + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnullc18 3 357.27 367.13 -175.63 351.27
## KgHaMTesdc18 6 360.59 380.32 -174.30 348.59 2.6713 3 0.4451## Data: subset(HRECSIOmit17, Treatment == "Cattle")
## Models:
## KgHaMTnullc18: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTtmic18: log(KgHa + 1) ~ TSF * Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnullc18 3 357.27 367.13 -175.63 351.27
## KgHaMTtmic18 8 303.52 329.83 -143.76 287.52 63.745 5 2.04e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit17, Treatment == "Cattle")
## Models:
## KgHaMTtsfc18: log(KgHa + 1) ~ TSF + (1 | Location)
## KgHaMTtmic18: log(KgHa + 1) ~ TSF * Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTtsfc18 4 303.50 316.65 -147.75 295.50
## KgHaMTtmic18 8 303.52 329.83 -143.76 287.52 7.976 4 0.09246 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit18, Treatment == "Sheep")
## Models:
## KgHaMTnulls18: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTtsfs18: log(KgHa + 1) ~ TSF + (1 | Location)
## KgHaMTmonths18: log(KgHa + 1) ~ Month + (1 | Location)
## KgHaMTesds18: log(KgHa + 1) ~ ESD + (1 | Location)
## KgHaMTtmis18: log(KgHa + 1) ~ TSF * Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnulls18 3 501.35 511.87 -247.68 495.35
## KgHaMTtsfs18 5 468.50 486.03 -229.25 458.50 36.852 2 9.944e-09 ***
## KgHaMTmonths18 6 506.61 527.64 -247.31 494.61 0.000 1 1.0000000
## KgHaMTesds18 7 493.16 517.69 -239.58 479.16 15.453 1 8.458e-05 ***
## KgHaMTtmis18 14 482.42 531.50 -227.21 454.42 24.736 7 0.0008451 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit18, Treatment == "Sheep")
## Models:
## KgHaMTnulls18: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTtsfs18: log(KgHa + 1) ~ TSF + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnulls18 3 501.35 511.87 -247.68 495.35
## KgHaMTtsfs18 5 468.50 486.03 -229.25 458.50 36.852 2 9.944e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit18, Treatment == "Sheep")
## Models:
## KgHaMTnulls18: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTmonths18: log(KgHa + 1) ~ Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnulls18 3 501.35 511.87 -247.68 495.35
## KgHaMTmonths18 6 506.61 527.64 -247.31 494.61 0.7437 3 0.8629## Data: subset(HRECSIOmit18, Treatment == "Sheep")
## Models:
## KgHaMTnulls18: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTesds18: log(KgHa + 1) ~ ESD + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnulls18 3 501.35 511.87 -247.68 495.35
## KgHaMTesds18 7 493.16 517.69 -239.58 479.16 16.197 4 0.002766 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit18, Treatment == "Sheep")
## Models:
## KgHaMTnulls18: log(KgHa + 1) ~ 1 + (1 | Location)
## KgHaMTtmis18: log(KgHa + 1) ~ TSF * Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTnulls18 3 501.35 511.87 -247.68 495.35
## KgHaMTtmis18 14 482.42 531.50 -227.21 454.42 40.932 11 2.475e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: subset(HRECSIOmit18, Treatment == "Sheep")
## Models:
## KgHaMTtsfs18: log(KgHa + 1) ~ TSF + (1 | Location)
## KgHaMTtmis18: log(KgHa + 1) ~ TSF * Month + (1 | Location)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## KgHaMTtsfs18 5 468.50 486.03 -229.25 458.50
## KgHaMTtmis18 14 482.42 531.50 -227.21 454.42 4.0799 9 0.9061