6.7.1: Using Minitab

Analysis of Variance and Design of Experiments · LibreTexts

0%

Contents

    Text

    Size
    100%
    Theme
    Typeface
    Line length
    Spacing

    From LibreTexts, under CC BY-NC 4.0, as the source states it; its equations are written in TeX, which the PDF shows typeset. This page at LibreTexts.

    In Minitab, specifying the mixed model is a little different.

    In Stat > ANOVA > General Linear Model > Fit General Linear Model

    we complete the dialog box:

    Minitab General Linear Model pop-up window with 'SR_score' in the Responses window and 'region school_type teacher' in the Factors window.
    Figure \(\PageIndex{1}\): General Linear Model pop-up window.

    We can create interaction terms under Model… by selecting "region" and "school_type" and clicking Add.

    Minitab General Linear Model: Model pop-up window with "region" and "school_type" selected in the Factors and Covariates window.
    Figure \(\PageIndex{2}\): General Linear Model: Model pop-up window.

    Finally, we create nested terms and effects are random under Random/Nest…:

    Minitab General Linear Model: Random Nest pop-up window, with "region 'school_type'" as entries next to "teacher" in the Nesting table, "region" as a fixed factor, "school_type" as a fixed factor, and "teacher" as a random factor.
    Figure \(\PageIndex{3}\): General Linear Model: Random Nest pop-up window.

    Minitab Output for the mixed model:

    Factor Information

    Factor Type Levels Values
    region Fixed 2 EastUS, WestUS
    school_type Fixed 2 Private, Public
    teacher(region school_type) Random 8 1(EastUS,Private), 2(EastUS,Private,)
    1(EastUS,Public), 2(EastUS, Public),
    1(WestUS, Private), 2(WestUS, Private),
    1(WestUS,Public), 2(WestUS,Public)

    Analysis of Variance

    Source DF Seq SS Adj SS Adj MS F-Value P-Value
    region 1 564.06 564.06 564.06 24.07 0.008
    school_type 1 76.56 76.56 76.56 3.27 0.145
    region*school_type 1 264.06 264.06 264.06 11.27 0.028
    teacher(region schoo_type) 4 93.75 93.75 23.44 5.00 0.026
    Error 8 37.50 37.50 4.69    
    Total 15 1035.94        

    Model Summary

    S R-sq R-sq(adj) R-sq(pred)
    2.16506 96.38% 93.21% 85.52%

    Minitab's results are in agreement with SAS Proc Mixed.

    This page titled 6.7.1: Using Minitab was last modified on Mon, 02 Jan 2023 23:40:32 GMT and is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by Penn State's Department of Statistics.