Fig 1.
General form of the data matrix for the Rasch model.
Fig 2.
Examinees-items map along the line characterizing the underlying continuum latent trait.
Fig 3.
A LogMAR chart for visual acuity testing, with 9 items.
Table 1.
The dichotomous response data matrix from a visual acuity test using the LogMAR chart in Fig 3, and the corresponding location estimates for patients and items.
Table 2.
Estimates of item location (in logits), in terms of difficulty to read, and the corresponding standard error, mean square (MNSQ) infits and outfits.
The fit statistics, highlighted in bold, are those exceeding the threshold of 1.5.
Table 3.
Estimates of patient location (in logit), in terms of visual acuity, and the corresponding standard error, mean square (MNSQ) infits and outfits.
The fit statistics, highlighted in bold, are those exceeding the threshold of 1.5.
Fig 4.
Patient-item map along the line characterizing their locations (in logit), in terms of visual acuity and difficulty to read, respectively.
Table 4.
QoV questionnaire: Symptoms, questions and response options.
Table 5.
Participants’ demographics.
Table 6.
Symptom location estimates (in logit), in terms of their level of prevalence within the cohort, and the corresponding standard errors, infits MNSQ and outfits MNSQ values, obtained from QoV questionnaire data collected one month post-operatively.
Fig 5.
Patient-symptom map for questionnaire data collected one month post-operatively.
Fig 6.
Item Characteristics Curves (ICC) for the questionnaire data collected one month post-operatively.
(a) ICC for Glare bothersome; (b) ICC for Starbursts bothersome; (c) ICC for Haloes bothersome; (d) ICC for Blurred vision bothersome; (e) ICC for Hazy vision bothersome; (f) ICC for Double images bothersome; (g) ICC for Fluctuation bothersome; (h) ICC for Difficulty in depth perception bothersome; (i) ICC for Distortion bothersome.
Table 7.
Patients’ location estimates (in logit), in terms of their perception of visual discomfort, and the corresponding standard errors, infit MNSQ and outfit MNSQ values, obtained from QoV questionnaire data collected one month post-operatively.
The patient IDs, highlighted in bold, correspond to the top 10 patients with the most visual discomfort, one year post-operatively.
Table 8.
Questionnaire responses and locations (in logit) for the top 10 patients, who experienced most discomfort with their vision, identified by the Rasch model from QoV questionnaire data collected one month post-operatively.
Table 9.
Symptoms’ locations estimates (in logit), in terms of their level of prevalence within the cohort, and the corresponding standard errors, infits MNSQ and outfits MNSQ values, obtained from QoV questionnaire data collected one year post-operatively.
Fig 7.
Patient-symptom map from QoV questionnaire data collected one year post-operatively.
Fig 8.
Item Characteristics Curves (ICC) for the questionnaire data collected one year post-operatively.
(a) ICC for Glare bothersome; (b) ICC for Starbursts bothersome; (c) ICC for Haloes bothersome; (d) ICC for Blurred vision bothersome; (e) ICC for Hazy vision bothersome; (f) ICC for Double images bothersome; (g) ICC for Fluctuation bothersome; (h) ICC for Difficulty in depth perception bothersome; (i) ICC for Distortion bothersome.
Table 10.
Patients’ location estimates (in logit), in terms of their perception of visual discomfort, and the corresponding standard errors, infit MNSQ and outfit MNSQ values, obtained from QoV questionnaire data collected one year post-operatively.
The patient IDs, highlighted in bold, correspond to the top 10 patients with the most visual discomfort, one month post-operatively.
Table 11.
Questionnaire responses and locations (in logit) for the top 10 patients, who experienced most discomfort with their vision identified by the Rasch model from QoV questionnaire data collected one year post-operatively.
Fig 9.
Location distributions of symptoms one month and one year post-operatively.
Fig 10.
(a) Location distributions of patients one month and one year post-operatively; (b) Distributions of patients percentage per group one month and one year post-operatively.
Fig 11.
Location distributions of the top 10 patients, who were most annoyed with their vision, one month and one year post-operatively.