BUG: sem() with level raised ValueError in pandas 1.2
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python
import pandas as pd
import numpy as np

idx = pd.MultiIndex.from_arrays([
    [str(i) for i in range(100)], np.random.choice(['A', 'B'], size=(100,))
], names=['a', 'b'])

data_dict = dict((str(i), np.random.rand(100)) for i in range(10))
data_dict['string'] = [str(i) for i in range(100)]
data_dict['bool'] = np.random.choice([True, False], (100,))
data = pd.DataFrame(data_dict, index=idx)

data.sem(level=1)
```

#### Problem description

Unexpected exception raised:

```
Traceback (most recent call last):
  File "/Users/wenjun/miniconda3/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3417, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-8-cd9abe134148>", line 1, in <module>
    data.sem(level=1)
  File "/Users/wenjun/miniconda3/lib/python3.8/site-packages/pandas/core/generic.py", line 10925, in sem
    return NDFrame.sem(self, axis, skipna, level, ddof, numeric_only, **kwargs)
  File "/Users/wenjun/miniconda3/lib/python3.8/site-packages/pandas/core/generic.py", line 10665, in sem
    return self._stat_function_ddof(
  File "/Users/wenjun/miniconda3/lib/python3.8/site-packages/pandas/core/generic.py", line 10655, in _stat_function_ddof
    return self._agg_by_level(
  File "/Users/wenjun/miniconda3/lib/python3.8/site-packages/pandas/core/generic.py", line 10552, in _agg_by_level
    return getattr(grouped, name)(**kwargs)
  File "/Users/wenjun/miniconda3/lib/python3.8/site-packages/pandas/core/groupby/groupby.py", line 1612, in sem
    result.iloc[:, cols] = result.iloc[:, cols] / np.sqrt(
  File "/Users/wenjun/miniconda3/lib/python3.8/site-packages/pandas/core/indexing.py", line 691, in __setitem__
    iloc._setitem_with_indexer(indexer, value, self.name)
  File "/Users/wenjun/miniconda3/lib/python3.8/site-packages/pandas/core/indexing.py", line 1636, in _setitem_with_indexer
    self._setitem_single_block(indexer, value, name)
  File "/Users/wenjun/miniconda3/lib/python3.8/site-packages/pandas/core/indexing.py", line 1860, in _setitem_single_block
    self.obj._mgr = self.obj._mgr.setitem(indexer=indexer, value=value)
  File "/Users/wenjun/miniconda3/lib/python3.8/site-packages/pandas/core/internals/managers.py", line 568, in setitem
    return self.apply("setitem", indexer=indexer, value=value)
  File "/Users/wenjun/miniconda3/lib/python3.8/site-packages/pandas/core/internals/managers.py", line 427, in apply
    applied = getattr(b, f)(**kwargs)
  File "/Users/wenjun/miniconda3/lib/python3.8/site-packages/pandas/core/internals/blocks.py", line 1025, in setitem
    values[indexer] = value
ValueError: shape mismatch: value array of shape (2,12) could not be broadcast to indexing result of shape (11,2)
```

#### Expected Output

Correct aggregation results shall be returned.

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : 3e89b4c4b1580aa890023fc550774e63d499da25
python           : 3.8.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.6.0
Version          : Darwin Kernel Version 19.6.0: Tue Nov 10 00:10:30 PST 2020; root:xnu-6153.141.10~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : zh_CN.UTF-8
pandas           : 1.2.0
numpy            : 1.19.1
pytz             : 2020.4
dateutil         : 2.8.1
pip              : 20.2.2
setuptools       : 49.6.0.post20200814
Cython           : 0.29.21
pytest           : 6.0.1
hypothesis       : None
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.17.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : 0.4.2
gcsfs            : None
matplotlib       : 3.2.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 1.0.1
pyxlsb           : None
s3fs             : None
scipy            : 1.5.0
sqlalchemy       : 1.3.18
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.51.2

</details>
