1 We fitted animal models to 38 years of song sparrow (Mel
2 ocarcinomas in women with unknown histology,
we fitted an age-cohort model to 8062 adenocarcinomas of
3 We fit data to a logistic-regression model predicting ea
4 We fit our data to a model that captures both single-par
5 We fit the results to a mass action model where the rate
6 We fitted a polyalanine-level model to all 3,757 ordered
7 We fit Cox proportional hazards models to assess the ass
8 To estimate VE,
we fit unconditional logistic regression models to calcu
9 We fit Cox proportional hazards models to calculate haza
10 We fitted fixed-effects models to compare siblings and c
11 We fitted logistic regression models to compare traffick
12 d number of typhoid fever cases in Blantyre,
we fit a mathematical model to culture-confirmed cases o
13 We fit mathematical models to data from experiments that
14 We fit the model to data on the passage of juvenile Paci
15 We fitted our model to data from in vitro clonal experim
16 We fitted the model to data from seven infected adults i
17 We fit the models to decadal subsets of the full (1958-2
18 We fitted multivariate logistic regression models to der
19 We fit a latent mixture model to eight experiments on tw
20 We fitted multivariable linear regression models to esti
21 We fit a Poisson model to estimate the risk of HO-CDI as
22 We fit logistic mixed-effects models to estimate the poo
23 We fit logistic regression models to estimate the propor
24 We fitted Bayesian models to estimate probabilities asso
25 We fitted hierarchical models to estimate the prevalence
26 We fit linear regression models to examine the associati
27 We fitted Cox proportional hazards models to examine the
28 We fitted multivariable survival models to examine the a
29 We fit an explicit model to experimental data over a wid
30 We fit the model to experimental data from the literatur
31 In this study,
we fitted statistical models to explain landscape-scale
32 For each voxel,
we fitted a pRF model to fMRI signals measured while par
33 We fit these data to hierarchical empirical models and u
34 To calculate parameter values
we fit the model to histopathology measurements of the f
35 We fit regression models to identify traditional and HIV
36 al Practice Research Datalink with BMI data,
we fitted Cox models to investigate associations between
37 We fit the model to local data on latent tuberculosis pr
38 ify mechanisms determining HPV transmission,
we fitted nonlinear mechanistic models to longitudinal d
39 As an illustratory study,
we fit this model to measured data of porcine coronary a
40 tatistical inference for intractable models,
we fitted a nonlinear control model to posturographic me
41 We fit a monoexponential curve to pressure data beginnin
42 We fit the model to previously published data on develop
43 We fit the MVB model to real data from 59 individuals on
44 We fit this cascade model to responses of individual MT
45 We fit the data to shapes with different numbers of vert
46 We fitted models to short observed time series of flour
47 We fit several mathematical models to subject behavior t
48 We fit Bayesian observer models to subjects' performance
49 We fit Poisson harmonic regression models to surveillanc
50 We fit a log-linear model to the contingency table of sp
51 We fit a sine curve to the monthly frequency of deaths i
52 We fit forgetting functions to the data to predict when
53 We fit Gaussians to the neuronal responses to twelve dif
54 To predict future growth by age group,
we fit linear regression models to the historic incidenc
55 To predict future growth by age group,
we fit linear regression models to the historic incidenc
56 We fit logistic regression models to the promoters of 62
57 We fit model parameters to the shell pigmentation patter
58 We fit our model to the data using likelihood, and we se
59 We fit the data sets to the Monod-Wyman-Changeux model t
60 s scapularis) on mice (Peromyscus leucopus),
we fit the extended model to the best currently availabl
61 We fit the model directly to the acquired pause-time and
62 We fit the model to the spiking activity of bilateral ne
63 We fit these calculations to the corresponding experimen
64 We fitted an exponential survival model to the high- and
65 We fitted linear mixed models to the outcome measurement
66 To address potential survivorship bias,
we fitted Markov models to the distribution of discrete
67 We fitted a dynamic mathematical model to trial data and
68 We fit our model to two data sets.
69 We fitted the model to unitary current-voltage relations