I construct a liner model.But the results are either diffetent or same when the model be complicated or easy repectively. Is there someone know the reason?
This is the different results.
> lm_all <- lm(mtci_ac~sd_height+density+ORA+dry_weight+northess,data=at_growth)
> summary(lm_all)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.480e-01 3.984e-02 6.225 1.33e-07 ***
sd_height 1.106e-02 1.045e-02 1.058 0.295
density 1.006e-01 1.481e-01 0.679 0.501
ORA -3.397e-04 1.361e-03 -0.250 0.804
dry_weight 5.045e-06 1.636e-05 0.308 0.759
northess 5.077e-03 3.203e-02 0.159 0.875
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Signif. codes:
0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> anova(lm_all)
Analysis of Variance Table
Response: mtci_ac
Df Sum Sq Mean Sq F value Pr(>F)
sd_height 1 0.02525 0.0252488 3.3059 0.07555 .
density 1 0.00469 0.0046852 0.6135 0.43750
ORA 1 0.00006 0.0000560 0.0073 0.93214
dry_weight 1 0.00074 0.0007426 0.0972 0.75659
northess 1 0.00019 0.0001919 0.0251 0.87475
Residuals 46 0.35132 0.0076374
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This is the same results.
> lm_all <- lm(mtci_ac~sd_height,data=at_growth)
> anova(lm_all)
Analysis of Variance Table
Response: mtci_ac
Df Sum Sq Mean Sq F value Pr(>F)
sd_height 1 0.02525 0.0252488 3.5363 0.06587 .
Residuals 50 0.35700 0.0071399
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> summary(lm_all)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.261539 0.019209 13.62 <2e-16 ***
sd_height 0.013703 0.007287 1.88 0.0659 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
