def glmer(self, formula, family, lmerVar="glmer1"):
if os.path.exists(".rbridge-glmer.csv"):
os.remove(".rbridge-glmer.csv")
# Peform lmer
self.write("library(lmerTest)")
s = self.call("(%s <- glmer(%s, family=%s))" % (lmerVar, formula, family))
self.write('write.csv(summary(%s)$coef, ".rbridge-glmer.csv")' % lmerVar)
while not os.path.exists(".rbridge-glmer.csv"):
time.sleep(0.1)
# Try this a few times, because sometimes the csv hasn't been written
# yet
for i in range(10):
try:
dm = CsvReader(".rbridge-glmer.csv").dataMatrix()
break
except:
time.sleep(1)
dm.rename("f0", "effect")
dm.rename("Estimate", "est")
dm.rename("Std. Error", "se")
dm.rename("Z value", "z")
dm.rename("Pr(>|z|)", "p")
dm = dm.addField("estProb", dtype=float)
dm["estProb"] = 1.0 / (1.0 + np.exp(-dm["est"]))
return dm
def anova(self, model1, model2, anovaVar="aov1"):
"""
Performs a model comparison using the R `anova()` function. The models
should be fitted and given a name first, using `RBridge.lmer()`.
Arguments:
model1 -- The name of the first model.
model2 -- The name of the first model.
Keyword arguments:
anovaVar -- The R variable to store the `anova()` output in.
(default='aov1')
Returns:
A DataMatrix with the output for the model comparison.
"""
if os.path.exists(".rbridge-anova.csv"):
os.remove(".rbridge-anova.csv")
self.write("%s <- anova(%s, %s)" % (anovaVar, model1, model2))
self.call('write.csv(%s, ".rbridge-anova.csv")' % anovaVar)
while not os.path.exists(".rbridge-anova.csv"):
time.sleep(0.1)
# Try this a few times, because sometimes the csv hasn't been written
# yet
for i in range(10):
try:
dm = CsvReader(".rbridge-anova.csv").dataMatrix()
break
except:
time.sleep(1)
dm.rename("f0", "model")
return dm
def lmer(self, formula, lmerVar="lmer1"):
"""
descL
Performs a linear mixed-effects model, using the `lmer()` function
from `lme4`.
arguments:
formula:
desc: An R-style mixed-effects formula.
type: str
keywords:
lmerVar:
desc: The R variable to store the `lmer()` output in.
type: str
returns:
desc: A DataMatrix with the model output.
type: DataMatrix
"""
if os.path.exists(".rbridge-lmer.csv"):
os.remove(".rbridge-lmer.csv")
# Peform lmer
self.write("library(lmerTest)")
s = self.call("(%s <- lmer(%s))" % (lmerVar, formula))
self.write('write.csv(summary(%s)$coef, ".rbridge-lmer.csv")' % lmerVar)
while not os.path.exists(".rbridge-lmer.csv"):
time.sleep(0.1)
# Try this a few times, because sometimes the csv hasn't been written
# yet
for i in range(10):
try:
dm = CsvReader(".rbridge-lmer.csv").dataMatrix()
break
except:
time.sleep(1)
dm.rename("f0", "effect")
dm.rename("Estimate", "est")
dm.rename("Std. Error", "se")
dm.rename("t value", "t")
dm.rename("Pr(>|t|)", "p")
return dm
