How to analyze or interpret the R could output (Model type, Model fit, Test the estimated parameters, Analys Morans test ). Below is the output. I am new to R could.
#Fitting a multivariate model
model1 <- lm(Newdata$Technical~ Newdata$Females +Newdata$Males)
#model summary
summary(model1)
Call:
lm(formula = Newdata$Technical ~ Newdata$Females + Newdata$Males)
Residuals:
Min 1Q Median 3Q Max
-20.7803 -4.6382 -0.1126 3.9507 21.6656
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -3.28324 1.62300 -2.023 0.0438 *
Newdata$Females 0.00335 0.02509 0.134 0.8938
Newdata$Males 0.13509 0.02488 5.430 1.02e-07 ***
---
Signif. codes: 0 '' 0.001 '' 0.01 '' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.08 on 372 degrees of freedom
Multiple R-squared: 0.3539, Adjusted R-squared: 0.3504
F-statistic: 101.9 on 2 and 372 DF, p-value: < 2.2e-16
#Testing Spatial Autocorrelation
moran.lm<-lm.morantest(model1, W, alternative="two.sided")
print(moran.lm)
Global Moran I for regression residuals
data:
model: lm(formula = Newdata$Technical ~ Newdata$Females +
Newdata$Males)
weights: W
Moran I statistic standard deviate = 13.237, p-value < 2.2e-16
alternative hypothesis: two.sided
sample estimates:
Observed Moran I Expectation Variance
2
0.415039220 -0.003097760 0.000997879
#LM multiplier
LM<-lm.LMtests(model1, W, test=c("LMerr", "LMlag",
"RLMerr", "RLMlag"))
print(LM)
Lagrange multiplier diagnostics for spatial dependence
data:
model: lm(formula = Newdata$Technical ~ Newdata$Females +
Newdata$Males)
weights: W
LMerr = 169.36, df = 1, p-value < 2.2e-16
Lagrange multiplier diagnostics for spatial dependence
data:
model: lm(formula = Newdata$Technical ~ Newdata$Females +
Newdata$Males)
weights: W
LMlag = 136.39, df = 1, p-value < 2.2e-16
Lagrange multiplier diagnostics for spatial dependence
data:
model: lm(formula = Newdata$Technical ~ Newdata$Females +
Newdata$Males)
weights: W
RLMerr = 34.051, df = 1, p-value = 5.37e-09
Lagrange multiplier diagnostics for spatial dependence
data:
model: lm(formula = Newdata$Technical ~ Newdata$Females +
Newdata$Males)
weights: W
RLMlag = 1.0859, df = 1, p-value = 0.2974
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