Students’ lunch provided by school.

<p>Meal provided by school consisted of four vegetable dishes and rice, and was shared by ten students.</p

Test information curves.

<p>Ability signifies knowledge, attitude and behavior with respect to nutrition and food safety, estimated using the maximum-likelihood method. Ability in the item response theory model practically (though not exclusively) ranged from −3 to +3. The test information of knowledge dimension reached a peak when the ability was between 0 and 1; this indicates that the measurement exhibited highest discriminative power among students with moderate ability with respect to nutrition and food safety knowledge. By contrast, this questionnaire exhibited highest discriminative power among students with limited ability with respect to attitude and behavior.</p

Item characteristic curves.

<p>Each Item characteristic curve describes the item-specific relationship between the ability level (X-axis) and probability of the ‘correct’ response (Y-axis). Ability in the item response theory model practically (though not exclusively) ranged from −3 to +3. The difficulty parameter is the point on the ability scale that corresponds to a probability of a correct response of 50%. The discrimination parameter is the slope of each curve. For Likert-type attitude and practice items, polytomous item response model were applied (multiple curves within a single figure, each curve stands for the relationship between ability and probability of a certain response).</p

Research process flow chart.

<p>Research process flow chart.</p

Additional file 1: of Quantifying traditional Chinese medicine patterns using modern test theory: an example of functional constipation

S1. Longitudinal data used for the validation of the tool. With respect to variable names, T1, T2, and T3 prefix indicate baseline, 1st follow-up, and 2nd follow-up, respectively. I1 to I10 suffix indicate number of item. (XLSX 32 kb

Comparison of risk factors for gestational hypertension and pre-eclampsia.

<p>Comparison of risk factors for gestational hypertension and pre-eclampsia.</p

Incidence of gestational hypertension and pre-eclampsia by characteristics of participants in the OaK birth cohort.

<p>Incidence of gestational hypertension and pre-eclampsia by characteristics of participants in the OaK birth cohort.</p

Survival curves for cumulative incidences of gestational hypertension and pre-eclampsia, stratified by common risk factors.

<p>Survival curves stratified by BMI (a, b), parity and pre-eclampsia history (c, d), diabetes (e, f) and number of babies (g, h), adjusted by age, race, education, household income, smoking, folic acid supplementation, BMI, parity, pre-eclampsia history, conception through assisted reproductive technologies, diabetes, infant sex, and number of babies. Risk factors modified the average GA in women with GH and PE in similar patterns. The survival curves were left-shifted in high-risk women (overweight or obese, nulliparous, or with PE history) compared with those in low-risk women (normal-weight, parous, or without PE history). The curves for PE were also left-shifted compared with the curves for GH.</p

Comparison of outcomes in women with gestational hypertension and pre-eclampsia using logistic regression model.

<p>Comparison of outcomes in women with gestational hypertension and pre-eclampsia using logistic regression model.</p

Comparison of risk factors for early- and late-onset pre-eclampsia.

<p>Comparison of risk factors for early- and late-onset pre-eclampsia.</p