rm(list = ls())
setwd("c:/users/Paul/Documents/Rwork")
getwd()
## [1] "c:/users/Paul/Documents/Rwork"
library(readr)
library(qqplotr)
## Warning: package 'qqplotr' was built under R version 3.5.3
## Loading required package: ggplot2
##
## Attaching package: 'qqplotr'
## The following objects are masked from 'package:ggplot2':
##
## stat_qq_line, StatQqLine
library(lavaan)
## This is lavaan 0.6-3
## lavaan is BETA software! Please report any bugs.
library(car)
## Warning: package 'car' was built under R version 3.5.3
## Loading required package: carData
## Warning: package 'carData' was built under R version 3.5.2
library(carData)
#Load the mineralizationdata
mineralizationdata<- read.csv(file="mineralizationdata2.csv")
attach(mineralizationdata)
head(mineralizationdata)
## Site Deer.Trt Honeysuckle Week CtotalN TrttotalN sqrCtotalN
## 1 Bachelor Excl H week0 1.28 1.28 1.13
## 2 College Excl H week0 3.07 3.07 1.75
## 3 Kramer Excl H week0 3.80 3.80 1.95
## 4 Reinhert Excl H week0 1.69 1.69 1.30
## 5 Western Excl H week0 1.55 1.55 1.24
## 6 Bachelor Excl NH week0 1.50 1.50 1.22
## sqrTrttotalN ConNO3 TrtNO3 Dmin Dnitr Con...NO3 Trt..NO3 Dmin.1 sqDmin
## 1 1.13 0.21 0.21 0 0 16.42 16.42 0 0
## 2 1.75 1.15 1.15 0 0 37.37 37.37 0 0
## 3 1.95 0.33 0.33 0 0 8.68 8.68 0 0
## 4 1.30 0.37 0.37 0 0 21.82 21.82 0 0
## 5 1.24 0.13 0.13 0 0 8.65 8.65 0 0
## 6 1.22 0.41 0.41 0 0 27.40 27.40 0 0
## sqDnitri lgDmin lgDnitri
## 1 0 NA NA
## 2 0 NA NA
## 3 0 NA NA
## 4 0 NA NA
## 5 0 NA NA
## 6 0 NA NA
#t.test(Dmin)
#t.test(Dnitr)
#ggplot for Dmin
library(ggplot2)
ggplot(mineralizationdata, aes(x = sqDnitri, y = sqDmin, color = Week, shape=Honeysuckle)) +
geom_point()
#Run a lm on sqrCtotalN and sqrTrttoalN and check normality for the residuals
#Modeling the difference in mineralization
mineralizationdata<- read.csv(file="mineralizationdata.csv")
modelDmin<-lm(sqDmin~Week,data=mineralizationdata)
modelDmin2<-lm(sqDmin~Week*Honeysuckle,data=mineralizationdata)
summary(modelDmin)
##
## Call:
## lm(formula = sqDmin ~ Week, data = mineralizationdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -429.44 -92.57 -6.78 55.82 1345.59
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.584e-14 8.611e+01 0.000 1.000000
## Weekweek12 2.429e+02 1.218e+02 1.994 0.049906 *
## Weekweek16 3.996e+02 1.218e+02 3.281 0.001594 **
## Weekweek2 1.540e+01 1.218e+02 0.126 0.899707
## Weekweek20 3.269e+02 1.218e+02 2.684 0.009020 **
## Weekweek24 4.303e+02 1.218e+02 3.533 0.000721 ***
## Weekweek4 8.495e+01 1.218e+02 0.698 0.487659
## Weekweek8 9.301e+01 1.218e+02 0.764 0.447481
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 272.3 on 72 degrees of freedom
## Multiple R-squared: 0.2819, Adjusted R-squared: 0.2121
## F-statistic: 4.038 on 7 and 72 DF, p-value: 0.0008795
summary(modelDmin2)
##
## Call:
## lm(formula = sqDmin ~ Week * Honeysuckle, data = mineralizationdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -498.29 -120.18 -3.49 56.45 1276.56
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.225e-13 1.275e+02 0.000 1.00000
## Weekweek12 2.974e+02 1.802e+02 1.650 0.10383
## Weekweek16 4.647e+02 1.802e+02 2.578 0.01224 *
## Weekweek2 1.625e+01 1.802e+02 0.090 0.92845
## Weekweek20 3.393e+02 1.802e+02 1.883 0.06429 .
## Weekweek24 4.993e+02 1.802e+02 2.770 0.00732 **
## Weekweek4 1.008e+02 1.802e+02 0.559 0.57791
## Weekweek8 1.339e+02 1.802e+02 0.743 0.46023
## HoneysuckleNH -1.116e-13 1.802e+02 0.000 1.00000
## Weekweek12:HoneysuckleNH -1.091e+02 2.549e+02 -0.428 0.67007
## Weekweek16:HoneysuckleNH -1.302e+02 2.549e+02 -0.511 0.61126
## Weekweek2:HoneysuckleNH -1.696e+00 2.549e+02 -0.007 0.99471
## Weekweek20:HoneysuckleNH -2.497e+01 2.549e+02 -0.098 0.92228
## Weekweek24:HoneysuckleNH -1.381e+02 2.549e+02 -0.542 0.58996
## Weekweek4:HoneysuckleNH -3.171e+01 2.549e+02 -0.124 0.90138
## Weekweek8:HoneysuckleNH -8.180e+01 2.549e+02 -0.321 0.74933
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 285 on 64 degrees of freedom
## Multiple R-squared: 0.3008, Adjusted R-squared: 0.1369
## F-statistic: 1.836 on 15 and 64 DF, p-value: 0.04849
anova(modelDmin)
## Analysis of Variance Table
##
## Response: sqDmin
## Df Sum Sq Mean Sq F value Pr(>F)
## Week 7 2095634 299376 4.0375 0.0008795 ***
## Residuals 72 5338719 74149
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
anova(modelDmin2)
## Analysis of Variance Table
##
## Response: sqDmin
## Df Sum Sq Mean Sq F value Pr(>F)
## Week 7 2095634 299376 3.6860 0.002089 **
## Honeysuckle 1 83703 83703 1.0306 0.313849
## Week:Honeysuckle 7 56897 8128 0.1001 0.998148
## Residuals 64 5198119 81221
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
residDmin<-resid(modelDmin)
residDmin2<-resid(modelDmin2)
plot(residDmin)
hist(residDmin)
plot(residDmin2)
hist(residDmin2)
anova(modelDmin,modelDmin2)
## Analysis of Variance Table
##
## Model 1: sqDmin ~ Week
## Model 2: sqDmin ~ Week * Honeysuckle
## Res.Df RSS Df Sum of Sq F Pr(>F)
## 1 72 5338719
## 2 64 5198119 8 140600 0.2164 0.9869
modelDminaov <- aov(sqDmin~Week*Honeysuckle,data=mineralizationdata)
posthoc3 <- TukeyHSD(x=modelDminaov, 'Week', conf.level=0.95)
posthoc3
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = sqDmin ~ Week * Honeysuckle, data = mineralizationdata)
##
## $Week
## diff lwr upr p adj
## week12-week0 242.862 -156.492828 642.21683 0.5523489
## week16-week0 399.608 0.253172 798.96283 0.0497420
## week2-week0 15.402 -383.952828 414.75683 1.0000000
## week20-week0 326.857 -72.497828 726.21183 0.1883147
## week24-week0 430.301 30.946172 829.65583 0.0259246
## week4-week0 84.955 -314.399828 484.30983 0.9975832
## week8-week0 93.014 -306.340828 492.36883 0.9957422
## week16-week12 156.746 -242.608828 556.10083 0.9198897
## week2-week12 -227.460 -626.814828 171.89483 0.6324589
## week20-week12 83.995 -315.359828 483.34983 0.9977506
## week24-week12 187.439 -211.915828 586.79383 0.8198354
## week4-week12 -157.907 -557.261828 241.44783 0.9169581
## week8-week12 -149.848 -549.202828 249.50683 0.9359276
## week2-week16 -384.206 -783.560828 15.14883 0.0677032
## week20-week16 -72.751 -472.105828 326.60383 0.9991049
## week24-week16 30.693 -368.661828 430.04783 0.9999974
## week4-week16 -314.653 -714.007828 84.70183 0.2276424
## week8-week16 -306.594 -705.948828 92.76083 0.2565080
## week20-week2 311.455 -87.899828 710.80983 0.2388216
## week24-week2 414.899 15.544172 814.25383 0.0361680
## week4-week2 69.553 -329.801828 468.90783 0.9993320
## week8-week2 77.612 -321.742828 476.96683 0.9986409
## week24-week20 103.444 -295.910828 502.79883 0.9918631
## week4-week20 -241.902 -641.256828 157.45283 0.5573564
## week8-week20 -233.843 -633.197828 165.51183 0.5993896
## week4-week24 -345.346 -744.700828 54.00883 0.1385490
## week8-week24 -337.287 -736.641828 62.06783 0.1588273
## week8-week4 8.059 -391.295828 407.41383 1.0000000
plot(modelDminaov)
#Modeling the difference in nitrification
mineralizationdata<- read.csv(file="mineralizationdata.csv")
modelDnitr<-lm(sqDnitri~Week,data=mineralizationdata)
modelDnitr2<-lm(sqDnitri~Week*Honeysuckle,data=mineralizationdata)
summary(modelDnitr)
##
## Call:
## lm(formula = sqDnitri ~ Week, data = mineralizationdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -428.76 -94.33 -7.11 58.24 1347.10
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.867e-14 8.598e+01 0.000 1.000000
## Weekweek12 2.418e+02 1.216e+02 1.988 0.050588 .
## Weekweek16 3.979e+02 1.216e+02 3.272 0.001641 **
## Weekweek2 1.585e+01 1.216e+02 0.130 0.896676
## Weekweek20 3.235e+02 1.216e+02 2.661 0.009607 **
## Weekweek24 4.295e+02 1.216e+02 3.532 0.000723 ***
## Weekweek4 8.290e+01 1.216e+02 0.682 0.497549
## Weekweek8 9.478e+01 1.216e+02 0.779 0.438244
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 271.9 on 72 degrees of freedom
## Multiple R-squared: 0.2805, Adjusted R-squared: 0.2106
## F-statistic: 4.01 on 7 and 72 DF, p-value: 0.0009321
summary(modelDnitr2)
##
## Call:
## lm(formula = sqDnitri ~ Week * Honeysuckle, data = mineralizationdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -498.97 -119.41 -3.74 58.24 1276.71
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.192e-13 1.272e+02 0.000 1.00000
## Weekweek12 2.963e+02 1.799e+02 1.647 0.10447
## Weekweek16 4.652e+02 1.799e+02 2.586 0.01201 *
## Weekweek2 1.710e+01 1.799e+02 0.095 0.92458
## Weekweek20 3.335e+02 1.799e+02 1.854 0.06841 .
## Weekweek24 4.999e+02 1.799e+02 2.779 0.00716 **
## Weekweek4 9.688e+01 1.799e+02 0.538 0.59212
## Weekweek8 1.347e+02 1.799e+02 0.749 0.45671
## HoneysuckleNH -9.940e-14 1.799e+02 0.000 1.00000
## Weekweek12:HoneysuckleNH -1.091e+02 2.544e+02 -0.429 0.66951
## Weekweek16:HoneysuckleNH -1.347e+02 2.544e+02 -0.529 0.59847
## Weekweek2:HoneysuckleNH -2.504e+00 2.544e+02 -0.010 0.99218
## Weekweek20:HoneysuckleNH -1.992e+01 2.544e+02 -0.078 0.93784
## Weekweek24:HoneysuckleNH -1.408e+02 2.544e+02 -0.553 0.58199
## Weekweek4:HoneysuckleNH -2.795e+01 2.544e+02 -0.110 0.91288
## Weekweek8:HoneysuckleNH -7.988e+01 2.544e+02 -0.314 0.75458
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 284.5 on 64 degrees of freedom
## Multiple R-squared: 0.2999, Adjusted R-squared: 0.1358
## F-statistic: 1.828 on 15 and 64 DF, p-value: 0.04966
anova(modelDnitr)
## Analysis of Variance Table
##
## Response: sqDnitri
## Df Sum Sq Mean Sq F value Pr(>F)
## Week 7 2075024 296432 4.01 0.0009321 ***
## Residuals 72 5322451 73923
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
anova(modelDnitr2)
## Analysis of Variance Table
##
## Response: sqDnitri
## Df Sum Sq Mean Sq F value Pr(>F)
## Week 7 2075024 296432 3.6633 0.002189 **
## Honeysuckle 1 82815 82815 1.0234 0.315521
## Week:Honeysuckle 7 60733 8676 0.1072 0.997691
## Residuals 64 5178904 80920
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
residDnitr<-resid(modelDnitr)
residDnitr2<-resid(modelDnitr2)
plot(residDnitr)
hist(residDnitr)
plot(residDnitr2)
hist(residDnitr2)
anova(modelDnitr,modelDnitr2)
## Analysis of Variance Table
##
## Model 1: sqDnitri ~ Week
## Model 2: sqDnitri ~ Week * Honeysuckle
## Res.Df RSS Df Sum of Sq F Pr(>F)
## 1 72 5322451
## 2 64 5178904 8 143547 0.2217 0.9858
modelDnitriaov <- aov(sqDnitri~Week*Honeysuckle,data=mineralizationdata)
posthoc5 <- TukeyHSD(x=modelDnitriaov, 'Week', conf.level=0.95)
posthoc5
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = sqDnitri ~ Week * Honeysuckle, data = mineralizationdata)
##
## $Week
## diff lwr upr p adj
## week12-week0 241.753 -156.8630124 640.36901 0.5557961
## week16-week0 397.860 -0.7560124 796.47601 0.0507787
## week2-week0 15.846 -382.7700124 414.46201 1.0000000
## week20-week0 323.522 -75.0940124 722.13801 0.1966720
## week24-week0 429.523 30.9069876 828.13901 0.0259142
## week4-week0 82.902 -315.7140124 481.51801 0.9979053
## week8-week0 94.780 -303.8360124 493.39601 0.9951638
## week16-week12 156.107 -242.5090124 554.72301 0.9207594
## week2-week12 -225.907 -624.5230124 172.70901 0.6382942
## week20-week12 81.769 -316.8470124 480.38501 0.9980805
## week24-week12 187.770 -210.8460124 586.38601 0.8171146
## week4-week12 -158.851 -557.4670124 239.76501 0.9137564
## week8-week12 -146.973 -545.5890124 251.64301 0.9413752
## week2-week16 -382.014 -780.6300124 16.60201 0.0696955
## week20-week16 -74.338 -472.9540124 324.27801 0.9989581
## week24-week16 31.663 -366.9530124 430.27901 0.9999967
## week4-week16 -314.958 -713.5740124 83.65801 0.2246001
## week8-week16 -303.080 -701.6960124 95.53601 0.2676553
## week20-week2 307.676 -90.9400124 706.29201 0.2504028
## week24-week2 413.677 15.0609876 812.29301 0.0365192
## week4-week2 67.056 -331.5600124 465.67201 0.9994678
## week8-week2 78.934 -319.6820124 477.55001 0.9984674
## week24-week20 106.001 -292.6150124 504.61701 0.9904802
## week4-week20 -240.620 -639.2360124 157.99601 0.5617188
## week8-week20 -228.742 -627.3580124 169.87401 0.6236557
## week4-week24 -346.621 -745.2370124 51.99501 0.1340344
## week8-week24 -334.743 -733.3590124 63.87301 0.1639860
## week8-week4 11.878 -386.7380124 410.49401 1.0000000
plot(modelDnitriaov)
