Why are pvalue, fvalue and residuals not being displayed in this two way anova in R?
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1
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I tried to perform a 2 way anova for the lung data set.However, as you can see below, I am only receiving DF,Sum sq and Mean sq in the output and no data is displayed on residuals, pvalue and fvalue.
Kindly help me with this.
Earnestly,
summary(aov(volume~ method+subject+ method*subject))
summary(aov(volume~(method)+(subject)+(method)*(subject)))
Output:
> summary(aov(volume~(method)+(subject)+(method)*(subject)))
Df Sum Sq Mean Sq
method 2 1.0811 0.5406
subject 5 2.1828 0.4366
method:subject 10 0.8322 0.0832
r statistics lm summary anova
edited Nov 11 at 1:17
Simon
4,14883070
asked Nov 11 at 1:02
user10001876
645
add a comment |
up vote
1
down vote
favorite
I tried to perform a 2 way anova for the lung data set.However, as you can see below, I am only receiving DF,Sum sq and Mean sq in the output and no data is displayed on residuals, pvalue and fvalue.
Kindly help me with this.
Earnestly,
summary(aov(volume~ method+subject+ method*subject))
summary(aov(volume~(method)+(subject)+(method)*(subject)))
Output:
> summary(aov(volume~(method)+(subject)+(method)*(subject)))
Df Sum Sq Mean Sq
method 2 1.0811 0.5406
subject 5 2.1828 0.4366
method:subject 10 0.8322 0.0832
r statistics lm summary anova
edited Nov 11 at 1:17
Simon
4,14883070
asked Nov 11 at 1:02
user10001876
645
how many rows of data do you have? and Im guessing it shows if you remove the interaction term for example?
– Simon
Nov 11 at 1:10
The lung data frame has 18 rows and 3 columns.
– user10001876
Nov 11 at 1:15
add a comment |
up vote
1
down vote
favorite
up vote
1
down vote
favorite
I tried to perform a 2 way anova for the lung data set.However, as you can see below, I am only receiving DF,Sum sq and Mean sq in the output and no data is displayed on residuals, pvalue and fvalue.
Kindly help me with this.
Earnestly,
summary(aov(volume~ method+subject+ method*subject))
summary(aov(volume~(method)+(subject)+(method)*(subject)))
Output:
> summary(aov(volume~(method)+(subject)+(method)*(subject)))
Df Sum Sq Mean Sq
method 2 1.0811 0.5406
subject 5 2.1828 0.4366
method:subject 10 0.8322 0.0832
r statistics lm summary anova
edited Nov 11 at 1:17
Simon
4,14883070
asked Nov 11 at 1:02
user10001876
645
I tried to perform a 2 way anova for the lung data set.However, as you can see below, I am only receiving DF,Sum sq and Mean sq in the output and no data is displayed on residuals, pvalue and fvalue.
Kindly help me with this.
Earnestly,
summary(aov(volume~ method+subject+ method*subject))
summary(aov(volume~(method)+(subject)+(method)*(subject)))
Output:
> summary(aov(volume~(method)+(subject)+(method)*(subject)))
Df Sum Sq Mean Sq
method 2 1.0811 0.5406
subject 5 2.1828 0.4366
method:subject 10 0.8322 0.0832
r statistics lm summary anova
r statistics lm summary anova
edited Nov 11 at 1:17
Simon
4,14883070
asked Nov 11 at 1:02
user10001876
645
edited Nov 11 at 1:17
Simon
4,14883070
asked Nov 11 at 1:02
user10001876
645
edited Nov 11 at 1:17
Simon
4,14883070
edited Nov 11 at 1:17
Simon
4,14883070
edited Nov 11 at 1:17
Simon
4,14883070
4,14883070
asked Nov 11 at 1:02
user10001876
645
asked Nov 11 at 1:02
user10001876
645
asked Nov 11 at 1:02
user10001876
645
645
how many rows of data do you have? and Im guessing it shows if you remove the interaction term for example?
– Simon
Nov 11 at 1:10
The lung data frame has 18 rows and 3 columns.
– user10001876
Nov 11 at 1:15
add a comment |
how many rows of data do you have? and Im guessing it shows if you remove the interaction term for example?
– Simon
Nov 11 at 1:10
The lung data frame has 18 rows and 3 columns.
– user10001876
Nov 11 at 1:15
how many rows of data do you have? and Im guessing it shows if you remove the interaction term for example?
– Simon
Nov 11 at 1:10
how many rows of data do you have? and Im guessing it shows if you remove the interaction term for example?
– Simon
Nov 11 at 1:10
The lung data frame has 18 rows and 3 columns.
– user10001876
Nov 11 at 1:15
The lung data frame has 18 rows and 3 columns.
– user10001876
Nov 11 at 1:15
add a comment |
1 Answer
1
active
oldest
votes
up vote
5
down vote
The answer is found in the docs for the summary aov function:
For fits with a single stratum the result will be a list of ANOVA
tables, one for each response (even if there is only one response):
the tables are of class "anova" inheriting from class "data.frame".
They have columns "Df", "Sum Sq", "Mean Sq", as well as "F value" and
"Pr(>F)" if there are non-zero residual degrees of freedom.
In your case you have a fully saturated model. In terms of degrees of freedom, your model is using up 18 (1 for the model, 2 for the method factor, 5 for subject, and 10 for the interaction). Given you only have 18 rows of data, you have no residual degrees of freedom to actually test the model hypothesis
What you need to do is either get more data, or simplify the model (for example, remove the interaction)
answered Nov 11 at 1:20
Simon
4,14883070
It has something to do with replication
– user10001876
Nov 12 at 0:15
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
5
down vote
The answer is found in the docs for the summary aov function:
For fits with a single stratum the result will be a list of ANOVA
tables, one for each response (even if there is only one response):
the tables are of class "anova" inheriting from class "data.frame".
They have columns "Df", "Sum Sq", "Mean Sq", as well as "F value" and
"Pr(>F)" if there are non-zero residual degrees of freedom.
In your case you have a fully saturated model. In terms of degrees of freedom, your model is using up 18 (1 for the model, 2 for the method factor, 5 for subject, and 10 for the interaction). Given you only have 18 rows of data, you have no residual degrees of freedom to actually test the model hypothesis
What you need to do is either get more data, or simplify the model (for example, remove the interaction)
answered Nov 11 at 1:20
Simon
4,14883070
It has something to do with replication
– user10001876
Nov 12 at 0:15
add a comment |
up vote
5
down vote
The answer is found in the docs for the summary aov function:
For fits with a single stratum the result will be a list of ANOVA
tables, one for each response (even if there is only one response):
the tables are of class "anova" inheriting from class "data.frame".
They have columns "Df", "Sum Sq", "Mean Sq", as well as "F value" and
"Pr(>F)" if there are non-zero residual degrees of freedom.
In your case you have a fully saturated model. In terms of degrees of freedom, your model is using up 18 (1 for the model, 2 for the method factor, 5 for subject, and 10 for the interaction). Given you only have 18 rows of data, you have no residual degrees of freedom to actually test the model hypothesis
What you need to do is either get more data, or simplify the model (for example, remove the interaction)
answered Nov 11 at 1:20
Simon
4,14883070
It has something to do with replication
– user10001876
Nov 12 at 0:15
add a comment |
up vote
5
down vote
up vote
5
down vote
The answer is found in the docs for the summary aov function:
For fits with a single stratum the result will be a list of ANOVA
tables, one for each response (even if there is only one response):
the tables are of class "anova" inheriting from class "data.frame".
They have columns "Df", "Sum Sq", "Mean Sq", as well as "F value" and
"Pr(>F)" if there are non-zero residual degrees of freedom.
In your case you have a fully saturated model. In terms of degrees of freedom, your model is using up 18 (1 for the model, 2 for the method factor, 5 for subject, and 10 for the interaction). Given you only have 18 rows of data, you have no residual degrees of freedom to actually test the model hypothesis
What you need to do is either get more data, or simplify the model (for example, remove the interaction)
answered Nov 11 at 1:20
Simon
4,14883070
The answer is found in the docs for the summary aov function:
For fits with a single stratum the result will be a list of ANOVA
tables, one for each response (even if there is only one response):
the tables are of class "anova" inheriting from class "data.frame".
They have columns "Df", "Sum Sq", "Mean Sq", as well as "F value" and
"Pr(>F)" if there are non-zero residual degrees of freedom.
In your case you have a fully saturated model. In terms of degrees of freedom, your model is using up 18 (1 for the model, 2 for the method factor, 5 for subject, and 10 for the interaction). Given you only have 18 rows of data, you have no residual degrees of freedom to actually test the model hypothesis
What you need to do is either get more data, or simplify the model (for example, remove the interaction)
answered Nov 11 at 1:20
Simon
4,14883070
answered Nov 11 at 1:20
Simon
4,14883070
answered Nov 11 at 1:20
Simon
4,14883070
answered Nov 11 at 1:20
Simon
4,14883070
4,14883070
It has something to do with replication
– user10001876
Nov 12 at 0:15
add a comment |
It has something to do with replication
– user10001876
Nov 12 at 0:15
It has something to do with replication
– user10001876
Nov 12 at 0:15
It has something to do with replication
– user10001876
Nov 12 at 0:15
add a comment |
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how many rows of data do you have? and Im guessing it shows if you remove the interaction term for example?
– Simon
Nov 11 at 1:10
The lung data frame has 18 rows and 3 columns.
– user10001876
Nov 11 at 1:15