NOT significant.

You need a stats class

Model 1

Negative binomial regression Number of obs = 2,398

Wald chi2(14) = 884.99

Dispersion = mean Prob > chi2 = 0.0000

Log pseudolikelihood = -7559.2006 Pseudo R2 = 0.0235

(Std. Err. adjusted for 27 clusters in campaign_number)

Robust

number_killed Coef. Std. Err. z P>z [95% Conf. Interval]

female0_1 .0921835 .2252278 0.41 0.682 -.3492548 .5336218

numwoundmonth_lag -.0004275 .0008411 -0.51 0.611 -.002076 .001221

lnbd -.0020845 .0438223 -0.05 0.962 -.0879746 .0838057

number_terrorists_year .0122675 .0164681 0.74 0.456 -.0200093 .0445444

numkillmonth_lag .0024239 .0020701 1.17 0.242 -.0016335 .0064813

religion_impt .0027452 .0096134 0.29 0.775 -.0160968 .0215871

many_attackers_cat -.6574785 .3344121 -1.97 0.049 -1.312914 -.0020427

weapon0_1 .0060996 .0370542 0.16 0.869 -.0665252 .0787244

assassination0_1 -.2165313 .1235204 -1.75 0.080 -.4586269 .0255642

political -.2149538 .0939054 -2.29 0.022 -.399005 -.0309026

security -.8816511 .0919077 -9.59 0.000 -1.061787 -.7015153

t1 .0090545 .0132741 0.68 0.495 -.0169623 .0350713

t2 -.000077 .0000812 -0.95 0.343 -.0002362 .0000822

t3 1.36e-07 1.30e-07 1.04 0.296 -1.19e-07 3.90e-07

_cons 3.460524 .7422251 4.66 0.000 2.005789 4.915259

/lnalpha .5598168 .1334456 .2982682 .8213655

alpha 1.750352 .2335768 1.347523 2.273602

Model 2

Negative binomial regression Number of obs = 2,398

Wald chi2(15) = .

Dispersion = mean Prob > chi2 = .

Log pseudolikelihood = -7542.227 Pseudo R2 = 0.0257

(Std. Err. adjusted for 27 clusters in campaign_number)

Robust

number_killed Coef. Std. Err. z P>z [95% Conf. Interval]

1.female0_1 .8713702 .5772283 1.51 0.131 -.2599764 2.002717<...See full post

br />
v2x_gencs 1.674458 1.136496 1.47 0.141 -.5530326 3.901949

female0_1#c.v2x_gencs

1 -1.437427 1.285307 -1.12 0.263 -3.956581 1.081728

numwoundmonth_lag -.0003947 .0008564 -0.46 0.645 -.0020732 .0012838

lnbd -.0057017 .0411733 -0.14 0.890 -.0863999 .0749964

number_terrorists_year .0123497 .0143653 0.86 0.390 -.0158057 .0405052

numkillmonth_lag .0023283 .0020228 1.15 0.250 -.0016362 .0062929

religion_impt .0086122 .0085485 1.01 0.314 -.0081425 .025367

many_attackers_cat -.4856774 .3676681 -1.32 0.187 -1.206294 .2349389

weapon0_1 .0119349 .03483 0.34 0.732 -.0563307 .0802004

assassination0_1 -.2104922 .1264849 -1.66 0.096 -.4583981 .0374136

political -.1226906 .0972053 -1.26 0.207 -.3132095 .0678282

security -.8006774 .0775152 -10.33 0.000 -.9526045 -.6487503

t1 .004448 .0108953 0.41 0.683 -.0169064 .0258024

t2 -.0000363 .0000611 -0.59 0.552 -.0001561 .0000834

t3 6.47e-08 9.26e-08 0.70 0.485 -1.17e-07 2.46e-07

_cons 1.57673 .9727694 1.62 0.105 -.3298632 3.483323

/lnalpha .5453489 .1286941 .293113 .7975848

alpha 1.72521 .2220244 1.340594 2.220172

......and go on......