Structural Equation Model by haryanti ma https://padlet.com/haryantima/SEMGB6333 en-us 2017-05-02 01:54:10 UTC 2025-09-24 06:04:06 UTC hello@padlet.com Regression haryantima https://padlet.com/haryantima/SEMGB6333/wish/169317672 2017-05-02 01:58:08 UTC https://padlet.com/haryantima/SEMGB6333/wish/169317672 Variables and Symbols haryantima https://padlet.com/haryantima/SEMGB6333/wish/169320487 2017-05-02 02:22:08 UTC https://padlet.com/haryantima/SEMGB6333/wish/169320487 Confirmatory Factor Analysis (CFA) haryantima https://padlet.com/haryantima/SEMGB6333/wish/169334189 2017-05-02 05:02:29 UTC https://padlet.com/haryantima/SEMGB6333/wish/169334189 Exploratory Factor Analysis (EFA) haryantima https://padlet.com/haryantima/SEMGB6333/wish/169334254 2017-05-02 05:03:28 UTC https://padlet.com/haryantima/SEMGB6333/wish/169334254 Meaning of Confirmatory Factor Analysis (CFA) nurshahiraalwanimohdtaufik https://padlet.com/haryantima/SEMGB6333/wish/169347739 CFA adalah prosedur statistik multivarian yang digunakan untuk menguji sejauh mana pembolehubah diukur mewakili bilangan konstrudan adalah alat yang digunakan untuk mengesahkan atau menolak teori pengukuran.

Multivarian Analisis Data pula  merujuk kepada mana-mana teknik statistik digunakan untuk menganalisis data yang mempunyai lebih daripada satu pembolehubah.

-Nurshahira Alwani binti Mohd Taufik
-Ummu Taqiah binti Bahari]]> 2017-05-02 07:17:59 UTC https://padlet.com/haryantima/SEMGB6333/wish/169347739 CFA MEANING https://padlet.com/haryantima/SEMGB6333/wish/169347979 CFA is a validating the measurement model of latent (represented by ellipses shape) construct. A latent variable or “hidden” variable is generally thought of as variable that is not directly measurable or observable.

-Mira Khalisa
-Nur Fadzilah]]> 2017-05-02 07:19:54 UTC https://padlet.com/haryantima/SEMGB6333/wish/169347979 EFA https://padlet.com/haryantima/SEMGB6333/wish/169348420

  • EFA: “Determine nature and number of latent variables that account for observed variation and covariation among set of observed indicators (≈ items or variables)” 

    • –  In other words, what causes these observed responses? 
    • –  Summarize patterns of correlation among indicators 
    • –  Solution is an end (i.e., is of interest) in and of itself 
Mazliana Binti Md Said
Nurhafizah Binti Abdul Musid
]]> 2017-05-02 07:23:19 UTC https://padlet.com/haryantima/SEMGB6333/wish/169348420 Meaning of Explatory Factor Analysis (EFA) nurshahiraalwanimohdtaufik https://padlet.com/haryantima/SEMGB6333/wish/169348832 EFA dalah kaedah statistik yang digunakan untuk mendedahkan struktur yang mendasari set yang agak besar pembolehubah dan satu teknik dalam analisis faktor yang matlamat untuk mengukur secara keseluruhannya bagi mengenal pasti hubungan asas antara pembolehubah.

-Nurshahira Alwani binti Mohd Taufik
-Ummu Taqiah binti Bahari]]> 2017-05-02 07:26:18 UTC https://padlet.com/haryantima/SEMGB6333/wish/169348832 Variables and Symbols https://padlet.com/haryantima/SEMGB6333/wish/169349049 A : Covariance of residual
B: Residual/Error
C: Response Item
D: Regression
E: Latent Variable
F: Error in measurement - error depicted from each measuring item of variable
G: Correlation/Factor loading for second order construct
H: Main Construct
I: Endogenous construct - dependent variable
J: Exogenous construct- independent variable

-Mira Khalisa
-Nur Fadzilah


]]> 2017-05-02 07:27:58 UTC https://padlet.com/haryantima/SEMGB6333/wish/169349049 Variable and Symbols in SEM nurshahiraalwanimohdtaufik https://padlet.com/haryantima/SEMGB6333/wish/169349286 A: Corelations of residuals.
The corelation between 2 errors.

B: Error 
-Variance (serakan antara observed value dan predicted value (mean dengan data)) left over after prediction of a measured variable atau outliers (data ekstrem yang melebihi julat data yang didapati)
- Data yang tidak normal - jauh daripada curve.
- error mesti rendah if not, curve akan menjadi lebih besar dan susah untuk mencari tengah.

C: Observed Variables.

D: Regression or Directional Path

E: Latent Variable
A variable in the model that is not measured.  It is also called an unmeasured or unobserved variable or a factor.

F: Disturbance
Variance left over after prediction of a factor.
- Variance bagi unobserved variable.
- adalah something can give impact to the construct faktor luaran yang memberi direct impak kepada exogenous variable. Example: Jantina, Umur, etc.

G: Corelations or Directional Path 

H: Endogenous Variables 
A variable that is predicted by another variable or dependent variable.

I: Items or Elements bagi construct.

J: Exogenous Variable
Is variable that predicts other variables or Independent variable.

q18- external variables
-Nurshahira Alwani binti Mohd Taufik
-Ummu Taqiah binti Bahari]]> 2017-05-02 07:29:44 UTC https://padlet.com/haryantima/SEMGB6333/wish/169349286 Hani, Mardiah, Yuzee https://padlet.com/haryantima/SEMGB6333/wish/169349561 CFA
it is used to test whether measures of a construct are consistent with a researcher's understanding of the nature of that construct (or factor). first, resercher develops a hypothesis.
EFA
to identify factors based on data and to maximize the amount of variance explained.[16] The researcher is not required to have any specific hypotheses about how many factors will emerge, and what items or variables these factors will comprise

]]> 2017-05-02 07:31:50 UTC https://padlet.com/haryantima/SEMGB6333/wish/169349561 EFA MEANING https://padlet.com/haryantima/SEMGB6333/wish/169349666 Exploratory Factor Analysis is a statistical technique that is used to reduce data to a smaller set of summary variables and to explore the underlining theoretical structure of the phenomena.  It is used to identify the structure of the relationship between the variable and the respondent. 

-Mira Khalisa
-Nur Fadzilah]]> 2017-05-02 07:32:47 UTC https://padlet.com/haryantima/SEMGB6333/wish/169349666 CFA https://padlet.com/haryantima/SEMGB6333/wish/169349825
  • Rather than trying to determine the number of factors, and subsequently, what the factors mean (as in EFA), if you already know (or suspect) the structure of your data, you can use a confirmatory approach 
  • Confirmatory factor analysis (CFA) is a way to specify which variables load onto which factors 
  • The loadings of all variables not related to a given factor are then set to zero 
  • For a reasonable number of parameters, the factor correlation can be estimated directly from the analysis (rotations are not needed) 
    • Mazliana 
    Nurhafizah
    ]]>     2017-05-02 07:34:20 UTC https://padlet.com/haryantima/SEMGB6333/wish/169349825     Regression https://padlet.com/haryantima/SEMGB6333/wish/169349979
  • Can run regression analyses using SEM software 
  • Mathematics/computer algorithm used by SEM is different, but 
  • Parameter estimates will be identical or very close 
  • Note that fit will be perfect (number of observations and number of parameters are equal) 
  • Running in SEM buysyounothing 

    • »  but, nice analysis to start with (you can check against SPSS or SAS run) 
    • »  SEM allows multiple DVs 
    • »  SEM allows two-group (or multi-group) comparisons 
    • Mazliana 
    Nurhafizah
    ]]>     2017-05-02 07:35:27 UTC https://padlet.com/haryantima/SEMGB6333/wish/169349979     Variables and Symbols https://padlet.com/haryantima/SEMGB6333/wish/169350414 A=Correlation between error
    B=Error
    C=Observed variables-Elements
    D=Regression
    Hubungan antara lebih 2 variables
    E=Latent variable/Unobserved variable-Construct-Then akan dapat min
    F=Disturbance-faktor-faktor luaran yang memberi impact kepada exogenous
    G=Correlation-
    H=Endogenous variables
    I=Elements
    J=Exogenous variables-IV
    Q= External variable

    Mazliana
    Nurhafizah]]>     2017-05-02 07:39:12 UTC https://padlet.com/haryantima/SEMGB6333/wish/169350414     Ghani,Iqa, & Patma https://padlet.com/haryantima/SEMGB6333/wish/169350623 Variable & Symbol
    A: Covariens of residual
    B: Casual relation
    C : direct observe variable/dependent variable
    represeted as the effect of other variable.
    D: Factor loading mean multiple regression.
    Akibat dan kesan pada J&E (IV)
    E & J: Latent Variable (pembolehubah yang tiada hubungan langsung dengan )
    F: error term. iaitu ketidaktentuan hubungan pembolehubah
    G: Correation QOL to Funtional 
    H: Exogenous variable - Dependent variable for Physical, Emotional and functional
    I: element  ]]>     2017-05-02 07:40:32 UTC https://padlet.com/haryantima/SEMGB6333/wish/169350623     Regression https://padlet.com/haryantima/SEMGB6333/wish/169350834

    -Mira Khalisa
    -Nur Fadzilah]]>     2017-05-02 07:41:46 UTC https://padlet.com/haryantima/SEMGB6333/wish/169350834     Shakirah, Marlina & Aney aneyamin https://padlet.com/haryantima/SEMGB6333/wish/169356372
    A - Correlation
    B - Error
    C - Observe variable
    D - Regression
    E - Latent variable (unobserve variable)
    F - Disturbance
    G - Impact of one variable on another
    H - Endogenous
    I - Elements (observe variable)
    J - Latent variable]]>     2017-05-02 08:17:24 UTC https://padlet.com/haryantima/SEMGB6333/wish/169356372     Sulaiman https://padlet.com/haryantima/SEMGB6333/wish/169356464 Variable &Symbol

    A: Covariens of residual
    B : measurement error
    C : Observed variables
    D : regresi
    E  & J : latent variables
    F : disturbant
    G : korelasi
    H : dependant variable
    I : Elemen
    J : Unobserve variable]]>     2017-05-02 08:17:56 UTC https://padlet.com/haryantima/SEMGB6333/wish/169356464     annur_hanie https://padlet.com/haryantima/SEMGB6333/wish/169356831 2017-05-02 08:20:58 UTC https://padlet.com/haryantima/SEMGB6333/wish/169356831 variables and symbols https://padlet.com/haryantima/SEMGB6333/wish/169356967 A= korelasi
    B =  error
    C = observe varibles
    D= regression coefficient / factor loading
    E= construct
    F= distrubant / faktor luaran yang mungkin memberi kesan
    G=korelasi
    H= dependant varible
    I = elemen
    J=  unobserve varible

    ]]>     2017-05-02 08:22:00 UTC https://padlet.com/haryantima/SEMGB6333/wish/169356967