Develop a logistic regression model for predicting if the respondent is outgoing in adulthood. Use cross-validation to select the appropriate predictor variables. In order to estimate this model, you have to first handle missing observations using the missing or the imputation strategy.

 

ID	Age	Urban	Mother_Edu	Father_Edu	Siblings	Black	Hispanic	White	Christian	WomenPlace	Male	FamilySize	Self_Esteem	Height	Weight	Outgoing_Kid	Outgoing_Adult	HealthPlan	Income	Marital_Status	Education	WeeksEmployed	NumberSpouses
1	21	1	8	8	1	0	0	1	1	0	0	5		65
2	20	1	5	8	8	0	0	1	1	1	0	5	16	62	120	0	1	1	0	1	12	0	1
3	18	1	10	12	3	0	0	1	1	0	0	5	20			1	1	1	0	1	12	52	1
4	17	1	11	12	3	0	0	1	1	0	0	5		67	110	0	1
5	20	1	12	12	1	0	0	1	1	0	1	4	23	63	130
6	19	1	12	12	1	0	0	1	1	0	1	4	27	64	200	1	1	1	40000	1	16	52	1
7	15	1	12	12	1	0	0	1	1	0	1	3	26	65	131	0	1	1	25000	3	12	52	2
8	21	1	9	6	7	0	0	1	0	0	0	3	23	65	179	1	1	1	27400	3	13	52	2
9	16	1	12	10	4	0	0	1	1	0	1	6	26	66	145	1	1	1	52000	1	14	52	1
10	19	1	12	12	3	0	0	1	1	0	0	3	19	66	115	0	1
11	20	1	12	12	1	0	0	1	1	0	1	3		71	155	1	1	1	55000	0	16	52	0
12	20	1	15	12	3	0	0	1	1	0	0	3	30	66	118	0	1
13	21	1	12	16	2	0	0	1	1	0	1	5	25	71	180	0	1	1	60000	2	16	52	1
14	16	1	12	12	2	0	0	1	1	0	0	5	21	67	135	1	1	1	48000	2	18	52	1
15	15	1	12	12	1	0	0	1	1	0	1	4	23	73	185	1	0	1	0	1	16	0	1
16	21	1	12	12	3	0	0	1	1	0	0	4	25	63	130	1	1	1	38000	1	13	52	1
17	22	1	12	15	2	0	0	1	0	0	1	2	24	69	160	1	1	0	48000	0	13	52	1
18	21	1	12	16	2	0	0	1	0	0	1	1	28	69	155	1	1	1	120000	3	13	52	2
19	22	1	10	12	3	0	0	1	1	0	0	2	28	64	120	1	1