Hi @jdweaver ! Thanks for the feedback I appreciate it! So, you should not use
pandas.dropna() in such a context. The issue here is that you have missing values in your repeated measurements (= within variable), and therefore Pingouin will internally remove all the subjects with missing values using this function. This is a quite conservative method, but it's sadly the most appropriate when dealing with missing values in repeated measures ANOVA. I'd also suggest that you take a look at the last part of this jupyter notebook, which explains the different missing values removal strategies. Hope this helps! Thanks!
Hi All, curious if anyone else has run into this. I'm trying to assess an interaction for a mixed model with 2 between factors and 1 within factor. Based on the pairwise_ttests documentation I should be able to do something like this:
from pingouin import pairwise_ttests, read_dataset';
pin.pairwise_ttests(dv='Scores', within='Time', between=['Group', 'Time'], data=df);This code with the sample data executes fine, but files for my data, resulting in an IndexError: list index out of range.
Anyone encountered this before?
Full traceback below, version of pingouin I am running: 0.2.9
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-63-081c62e8ce0a> in <module>
4 , data=mix_melt_usage_cat_t6m_feb
5 ,padjust='holm', return_desc=True
----> 6 ,nan_policy='listwise'
7 )
C:\Anaconda\lib\site-packages\pingouin\pairwise.py in pairwise_ttests(data, dv, between, within, subject, parametric, alpha, tail, padjust, effsize, nan_policy, return_desc, interaction, export_filename)
360 stats = stats.append(pairwise_ttests(dv=dv,
361 between=fbt[i],
--> 362 within=fwt[i],
363 subject=subject,
364 data=data,
IndexError: list index out of range
Hi @jdweaver ! Two things: first you need to pass
subject as well whenever testing for a within-subject effect, 2) if your 'Time' column is a within-subject factor, do not put it in the between argument. The following should work: pin.pairwise_ttests(dv='Scores', within='Time', between='Group', subject='YOURSUBJECTVARIABLE', data=df)
@raphaelvallat thanks for clarifying. I've updated the syntax based on your suggestion. I'm not seeing the "within" factor show up in the contrasts. Based on the notes in the documentation it should show up as: within + between + within between
Is showing only the between factors when a within effect is specified, expected behavior? *
Sample code below:
Sample code below:
pin.pairwise_ttests(dv='outcome'
,within='variable'
,between=['between1', 'between2']
,subject='subjectvariable'
, data=df
)
this is a figure obtained with the new shift plot version (0.3.0). it's different from the figure on the website (https://pingouin-stats.org/generated/pingouin.plot_shift.html#pingouin.plot_shift). e.g. if Y values are smaller than X values, quantiles are positive (should be negative), because it's Y minus X.
so the figure on your website is not correct?
import numpy as np
import pingouin as pg
np.random.seed(42)
x = np.random.normal(5.5, 2, 50)
y = np.random.normal(6, 1.5, 50)
fig = pg.plot_shift(x, y)
import pingouin as pg
np.random.seed(42)
x = np.random.normal(5.5, 2, 50)
y = np.random.normal(6, 1.5, 50)
fig = pg.plot_shift(x, y)
so this is the example from your website. as you can see, the plot is different from yours :-)
and i tried the second example from your website too:
import numpy as np
import pingouin as pg
np.random.seed(42)
x = np.random.normal(5.5, 2, 30)
y = np.random.normal(6, 1.5, 30)
fig = pg.plot_shift(x, y, paired=True, n_boot=2000,
percentiles=[25, 50, 75],
show_median=False, seed=456, violin=False)
import pingouin as pg
np.random.seed(42)
x = np.random.normal(5.5, 2, 30)
y = np.random.normal(6, 1.5, 30)
fig = pg.plot_shift(x, y, paired=True, n_boot=2000,
percentiles=[25, 50, 75],
show_median=False, seed=456, violin=False)
different from your figure
Thanks for your sharp eyes @manfredh_twitter ! So indeed I think there are two separate issues here:
1) The y-label is not correct, it should be X - Y
2) For some reasons, the figure on Pingouin's website were not updated when I released the latest version.
I'll try to fix that soon!
1) The y-label is not correct, it should be X - Y
2) For some reasons, the figure on Pingouin's website were not updated when I released the latest version.
I'll try to fix that soon!
so it's only another depiction. or is there some deeper meaning?
Hi pingouin users! I'm working with the mediation_analysis function and am wondering if there is any way to incorporate repeated measures data? Perhaps via mixed effects?
Currently, I have X_t1, M_t1, and Y_t2 as my variables (where _t1 and _t2 represents the variable assessed at timepoint 1 or timepoint 2, respectively). If I only use these three variables, then the model is fine because no two variables have dependency due to repeated measurement (i.e., I'm only using Y_t2, not Y_t1 and Y_t2 in model; similarly, I only use X_t1, not X_t1 and X_t2). But I would like to include Y_t1 as a covariate, which introduces correlated data into the model.
Currently, I have X_t1, M_t1, and Y_t2 as my variables (where _t1 and _t2 represents the variable assessed at timepoint 1 or timepoint 2, respectively). If I only use these three variables, then the model is fine because no two variables have dependency due to repeated measurement (i.e., I'm only using Y_t2, not Y_t1 and Y_t2 in model; similarly, I only use X_t1, not X_t1 and X_t2). But I would like to include Y_t1 as a covariate, which introduces correlated data into the model.
Hi @LindenParkes_twitter! Unfortunately, this is not possible right now in Pingouin, and I doubt that it will be in the near future. From my understanding, there does not seem to be a gold standard to do mediation analyses with repeated measures, even though some methods have been developed in recent years (e.g. http://afhayes.com/public/aps2015mh.pdf). Alternatively, you can perhaps regress your covariate
Y_t2 to all the other variables separately, get the residuals, and then apply a mediation on the residuals...?
Hi @manfredh_twitter ! I just pushed a commit on the develop branch to fix the plot_shift function, which now returns the Y - X quantiles (in other words, I did not change the label to X - Y, but instead I changed the code to calculate the Y - X quantile, as it was before v0.3.0, but still keeping the robust estimator implemented in v0.3.0). This will be released in the next stable version of Pingouin, but if by any chance you can try the new function on your own data with the develop version of Pingouin (cloned from GitHub, then switch to the develop branch then
python setup.py develop), that would be fantastic! Thank you! Commit: raphaelvallat/pingouin@774a5c4
it works! btw: thats my own implementation of shift plot (for personal use), so that i can add labels and change colors...
np.random.seed(42)
x = np.random.normal(5.5, 2, 50)
y = np.random.normal(6, 1.5, 50)
fig = sp.shift_plot(x, y, n_boot=5000, percentiles=[25, 50, 75],
ci=0.95, show_median=True, show_mean=False, violin=True,
xlab="Item X", ylab="Item Y", score="Preferenceranking",
size=2)
x = np.random.normal(5.5, 2, 50)
y = np.random.normal(6, 1.5, 50)
fig = sp.shift_plot(x, y, n_boot=5000, percentiles=[25, 50, 75],
ci=0.95, show_median=True, show_mean=False, violin=True,
xlab="Item X", ylab="Item Y", score="Preferenceranking",
size=2)
23 b
^
this name worked perfectly in rm_corr
I get also this error for other strings. I don't understand why some are ok and other not?
tks for your help!
Hi @garincle, this is surprising. First, the error is not caused by Pingouin but by an internal call to statsmodels and patsy. I'd therefore recommend you upgrade these two libraries. Second, a "b" before a string means that the string is encoded as bytes. However, in this case the "b" is at the end of the string so I really don't see why you would get an error here. Could you send a list of strings that work and strings that do not work? Anyway, for now I think the quickest fix is to rename your variable (e.g. y="Region"). Thanks
Don't works
8Bm
23c
14r
11l
24a_prime
works
STGr
CA1
Clear
MGad
MGmc
MGz
MGpd
OT
Iapl
Ri
it seems that starting with a number cause the problem
all packages are already up to date