SPSS

Full course: https://www.youtube.com/watch?v=ZpwZS3XnEZA#t=8m41s 

samples: https://www.youtube.com/watch?v=ZpwZS3XnEZA#t=16m22s c:program filesibmspsssp26samplesdemo.sav 18m50s:Descriptive Stat|Explore 19m36s:basic graph, 20m48s(https://drive.google.com/drive/folders/1LCtTh6Gt2PqFSLlUt_z2Mhu3Ha-KFujT)

0. Original papers/Installation

網上找老友的spss 26.zip，與Python 3.4一起裝在W11下，sample下例子還沒學。複原了這兩篇文章的結果：線性混合效應模型入門之一（linear mixed effects model）線性混合效應模型入門之二 原始數據：https://pan.baidu.com/s/1PYcMxDYgjjSvv9seUXmIDg?pwd=ngkw

SPSS 26 documents：https://www.ibm.com/docs/en/spss-statistics/26.0.0

本案例數據來源於一個腎髒病的研究。研究對200個腎病患者進行隨訪，每年化驗一次腎小球濾過率（GFR，評價腎髒功能的指標，會逐年下降）。主要分析目的是探索基線的尿蛋白定量對GFR年下降率（斜率）的影響（尿蛋白量越大，對腎功能危害越大），混雜因素包括基線年齡和性別。

The data in this case come from a study on kidney disease. The study followed 200 patients with kidney disease and tested the glomerular filtration rate (GFR, an indicator of kidney function, which decreases year by year) once a year. The main purpose of the analysis was to explore the impact of baseline urinary protein quantification on the annual decline rate (slope) of GFR (the greater the amount of urinary protein, the greater the harm to renal function). Confounding factors include baseline age and gender.

字段說明：
（1）patient: 患者ID編號；
（2）visit：化驗次序編號；
（3）time：化驗時間（單位年），第一次化驗定為0，後麵依次推延；
（4）GFR：腎小球濾過率，單位是ml/min/1.73^2，作為響應變量；
（5）age：基線年齡，單位歲；
（6）gender：性別，0=男，1=女；
（7）micro：基線是否有微量蛋白尿，0=無，1=有；
（8）macro：基線是否有大量蛋白尿，0=無，1=有；
補充說明：
（1）蛋白尿這裏用了啞變量編碼，macro=0且micro=0表示沒有蛋白尿；
（2）數據中GFR化驗數據有缺失，線性混合效應模型對缺失數據有良好的處理能力。

1. SPSS start note

1. Rub SPSS, close welcome window, operate on main GUI.
2. File|Import Data|CSV Data, Open .csv file, then click OK

3. Analyze|Mixed Models|Linear,

4. Set model, start by choose patient from left, use arraw to add to right pane, Continue (below left)

5. Add factors, as shown at above right, click Fixed.
6. Add fixed effect as shown above. Select multiple params for interaction *. Click Continue.

7. Set Covariance Type and other factors as shown below left. Click Continue.

 

8. Click Estimation, change method as shown above right, then click Continue.
9. Click Statistics, then Save, both with Continue after settings, shown below, then OK!

 

10. Outputs items shown at the light and details at the right, for example:

11. Click Disk symbol to save it: