I work on antifungal activity of some molecules ("cyclo") added with fungicides and I want to assess impact of these cyclos and their concentration ratio. CMI is a quantitative variable and all other variables are factors.
I have this script:
mod=lmer(CMI ~ cyclo*ratio + (1|fungicide) + (1|strains), data)
And I'd like to know if I can use tbl_regression() (library(gtsummary)) with my lmer()?
If yes, what do I have to specify for exponentiate term ?
If I write exponentiate=FALSE I obtain the same values than the estimates in the classical summary(mod).
Thank you for your help
Steffi
The default behavior for tbl_regression() for a mixed-effects models is to print the fixed-effects only. To see the full output, including the random components, you need to override the default function for tidying up the model results using the tidy_fun= argument.
library(gtsummary)
lme4::lmer(age ~ marker + (1|grade), trial) %>%
tbl_regression(
# set the tidying function to broom.mixed::tidy to show random effects
tidy_fun = broom.mixed::tidy,
)
You can use the label= argument to update the label displayed for the random components if you wish.
The default is exponentiate = FALSE, so you don't need specify in the tbl_regression() call.
For more details on the tidy_fun= argument, you can review this help file: http://www.danieldsjoberg.com/gtsummary/reference/vetted_models.html
Hope this helps! Happy Coding!
Related
I want to create a variable called 'flag_artifact' where certain subjects from my dataset (for whom I know have bad quality images) are coded as e.g., 1. My dataset is stored in a table T with a certain number of rows and 'subject' is the 1st column in the table.
I managed to do it by creating a for loop. Surely there is a more efficient way to do this by perhaps directly creating the variable and using less lines of code? Could anyone give some advice?
Thank you very much! Here is what I have:
flag_artifact = {'T_300'}; %flagging subject number 300 for example
for i = 1:size(T,1)
if isequal(table2cell(T(i, 1)), flag_artifact)
T(i, 1) = {'1'};
end
end
However, when creating the variable flag_artifact = {'T_300'}, I would like it to include more than one subject. I tried using flag_artifact = {'T_300'}; {'T_301'}, as well as flag_artifact = {'T_300', 'T_301'} but it doesn't work because these subject identifiers do not get replaced with 1s.
I've had great success using the gtsummary::tbl_regression function to display regression model results. I can't see how to use tbl_regression with pooled regression models from imputed data sets, however, and I'd really like to.
I don't have a reproducible example handy, I just wanted to see if anyone else has found a way to work with, say, mids objects created by the mice package in tbl_regression.
In the current development version of gtsummary, it's possible to summarize models estimated on imputed data from the mice package. Here's an example
# install dev version of gtsummary
remotes::install_github("ddsjoberg/gtsummary")
library(gtsummary)
packageVersion("gtsummary")
#> [1] ‘1.3.5.9012’
# impute the data
df_imputed <- mice::mice(trial, m = 2)
# build the model
imputed_model <- with(df_imputed, lm(age ~ marker + grade))
# present beautiful table with gtsummary
tbl_regression(imputed_model)
#> pool_and_tidy_mice: Tidying mice model with
#> `mice::pool(x) %>% mice::tidy(exponentiate = FALSE, conf.int = TRUE, conf.level = 0.95)`
Created on 2020-12-16 by the reprex package (v0.3.0)
It's important to note that you pass the mice model object to tbl_regression() BEFORE you pool the results. The tbl_regression() function needs access to the individual models in order to correctly identify the reference row and variable labels (among other things). Internally, the tidying function used on the mice model will first pool the results, then tidy the results. The code used for this process is printed to the console for transparency (as seen in the example above).
GAMS: I think I have a pretty simple question, however I'm stuck and was wondering if someone could help here.
A simplified version of my model looks like this:
set(i,t) ;
parameter price
D;
variable p(i,t)
e(i,t);
equations
Equation1
obj.. C=sum((i,t), p(i,t)*price);
Model file /all/ ;
Solve file minimizing C using MIP ;
Display C.l;
p(i,t) and e(i,t) are related:
Equation1 .. e(i,t)=e=e(i,t-1)+p(i,t)*D
Now I want to retrieve information from the solution: lets say I want to know at what t e(i,t) has a certain value for example --> e(i,t)= x(i) or otherwise formulated e(i,t=TD)=x(i) find TD, where x(i) thus is depending on i. Does anyone know how I can write this in to my GAMs model? To be clear I do not want to change anything about my solution and the model I have runs; I just want to retrieve this information from the solution given.
So far I tried a couple of thing and nothing worked. I think that this must be simple, can anyone help? Thank you!
Try something like this:
set i /i1*i10/
t /t1*t10/;
variable e(i,t);
*some random dummy "solution"
e.l(i,t) = uniformInt(1,10);
set find5(i,t) 'find all combinations of i and t for which e.l=5';
find5(i,t)$(e.l(i,t)=5) = yes;
display e.l,find5;
Hope that helps,
Lutz
I am trying to find a better solution to calculation using data stored in table. I have a large table with many variables (100+) from which I select smaller sub-table with only two observations and their difference for smaller selection of variables. Thus, the resulting table looks for example similarly to this:
air bbs bri
_________ ________ _________
test1 12.451 0.549 3.6987
test2 10.2 0.47 3.99
diff 2.251 0.078999 -0.29132
Now, I need to multiply the ‘diff’ row with various coefficients that differ between variables. I can get the same result with the following code:
T(4,:) = array2table([T.air(3)*0.2*0.25, T.bbs(3)*0.1*0.25, T.bri(3)*0.7*0.6/2]);
However, I need more flexible solution since the selection of variables will differ between applications. I was thinking that better solution might be using either varfun or rowfun and speficic function that would assign correct coefficients/equations based on variable names:
T(4,:) = varfun(#func, T(3,:), 'InputVariables', {'air' 'bbs' 'bri'});
or
T(4,:) = rowfun(#func, T(3,:), 'OutputVariableNames', T.Properties.VariableNames);
However, the current solution I have is similarly inflexible as the basic calculation above:
function [air_out, bbs_out, bri_out] = func(air, bbs, bri)
air_out = air*0.2*0.25;
bbs_out = bbs*0.1*0.25;
bri_out = bri*0.7*0.6/2;
since I need to define every input/output variable. What I need is to assign in the function coefficients/equations for every variable and the ability of the function to apply it only to the variables that are present in the specific sub-table.
Any suggestions?
I've been looking throught the documentation, but can't seem to find the bit I want.
I have a for loop and I would like to be able to view every value in the for loop.
for example here is a part of my code:
for d = 1 : nb
%for loop performs blade by blade averaging and produces a column vector
for cc = navg : length(atbmat);
atb2 = (sum(atbmat((cc-(navg-1):cc),d)))/navg;
atbvec2(:,cc) = atb2;
end
%assigns column vector 'atbvec2' to the correct column of the matrix 'atbmat2'
atbmat2(d,1:length(atbvec2)) = atbvec2;
end
I would like to view every value of atb2. I'm a python user(new to MATLAB) and would normally use a simple print statement to find this.
I'm sure there is a way to do it, but I can't quite find how.
Thankyou in advance.
you can use disp in Matlab to print to the screen but you might want to use sprintf first to format it nicely. However for debugging you're better off using a break point and then inspect the variable in the workspace browser graphically. To me, this is one of Matlab's best features.
Have a look at the "Examine Values" section of this article
The simplest way to view it everywhere is to change this line:
atb2 = (sum(atbmat((cc-(navg-1):cc),d)))/navg;
Into this, without semicolon:
atb2 = (sum(atbmat((cc-(navg-1):cc),d)))/navg
That being said, given the nature of your calculation, you could get the information you need as well by simply storing every value of abt2 and observing them afterwards. This may be done in atbmat2 already?
If you want to look at each value at the time it happens, consider setting a breakpoint or conditional breakpoint after the line where abt2 is assigned.