So how does Item Response Theory actually work? To model the precision terjemahan - So how does Item Response Theory actually work? To model the precision Bahasa Indonesia Bagaimana mengatakan

So how does Item Response Theory ac

So how does Item Response Theory
actually work? To model the precision of
a scale across the trait range, we need to
know about two distinct parameters of
each item. These are item difficulty and
item discrimination. Stated formally, the
logic behind a two-parameter logistic
item response model (2PLM; Birnbaum,
1968) can be summarized as follows:
(1.0) Pj
(θi
) = 1 / (1 + exp(-αj
(θi
- βj
)))
This equation states that the
probability that a given individual (j)
with a given level of trait θ will have
a level of that trait defined by one
aspect of the person (their true trait
level), and two aspects of the way it is
measured (or item parameters). These
two parameters are item difficulty (βj
)
and item discrimination (αj
). In this
model, trait levels can be thought of
as reflecting a standardized (z-scored)
range, with a Mean of 0 and Standard
Deviation of 1.
Item difficulty reflects the level of
the trait that a person would need to
have a 1 in 2 (50%) chance of scoring
in the positive direction on the item.
For example, a person with the sample
mean level of a trait (θ = 0), would have
a 50% chance of scoring in the positive
(high trait) direction on an item with a
difficulty value of 0. Similarly, a person
with a trait level one unit above the
mean (θ = 1), would have a 50% chance
of scoring in the positive (high trait)
direction on an item with a difficulty
value of 1.
0/5000
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So how does Item Response Theory actually work? To model the precision of a scale across the trait range, we need to know about two distinct parameters of each item. These are item difficulty and item discrimination. Stated formally, the logic behind a two-parameter logistic item response model (2PLM; Birnbaum, 1968) can be summarized as follows:(1.0) Pj(θi) = 1 / (1 + exp(-αj(θi - βj)))This equation states that the probability that a given individual (j) with a given level of trait θ will have a level of that trait defined by one aspect of the person (their true trait level), and two aspects of the way it is measured (or item parameters). These two parameters are item difficulty (βj) and item discrimination (αj). In this model, trait levels can be thought of as reflecting a standardized (z-scored) range, with a Mean of 0 and Standard Deviation of 1. Item difficulty reflects the level of the trait that a person would need to have a 1 in 2 (50%) chance of scoring in the positive direction on the item. For example, a person with the sample mean level of a trait (θ = 0), would have a 50% chance of scoring in the positive (high trait) direction on an item with a difficulty value of 0. Similarly, a person with a trait level one unit above the mean (θ = 1), would have a 50% chance of scoring in the positive (high trait) direction on an item with a difficulty value of 1.
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Jadi bagaimana Teori Barang Response
benar-benar bekerja? Untuk model ketepatan
skala di berbagai sifat, kita perlu
tahu tentang dua parameter yang berbeda dari
setiap item. Ini adalah item yang kesulitan dan
diskriminasi item. Menyatakan secara resmi, yang
logika di balik dua parameter logistik
Model respon item (2PLM; Birnbaum,
1968) dapat disimpulkan sebagai berikut:
(1.0) Pj
(θi) = 1 / (1 ​​+ exp (-αj (θi - βj)) ) Persamaan ini menyatakan bahwa probabilitas bahwa individu tertentu (j) dengan tingkat tertentu θ sifat akan memiliki tingkat yang sifat didefinisikan oleh salah satu aspek dari orang (sifat sejati mereka tingkat), dan dua aspek cara itu diukur (atau parameter item). Ini dua parameter yang item yang kesulitan (βj) dan diskriminasi item (αj). Dalam Model, tingkat sifat dapat dianggap sebagai mencerminkan standar (z-mencetak) Kisaran, dengan mean 0 dan Standar Deviasi dari 1. Barang kesulitan mencerminkan tingkat sifat bahwa seseorang akan perlu memiliki 1 di 2 (50%) kesempatan mencetak gol ke arah positif pada item. Misalnya, orang dengan sampel berarti tingkat sifat (θ = 0), akan memiliki kesempatan 50% dari mencetak gol di positif (sifat tinggi) arah pada item dengan nilai kesulitan 0. Demikian pula, orang dengan tingkat sifat satu unit di atas rata-rata (θ = 1), akan memiliki kesempatan 50% dari mencetak gol di positif (sifat tinggi) arah pada item dengan kesulitan nilai 1.
































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